{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 21,
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: tensorflow in c:\\users\\fer_u\\pycharmprojects\\cyberattacksattention\\venv\\lib\\site-packages (2.11.0)\n",
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      "Requirement already satisfied: importlib-metadata>=4.4 in c:\\users\\fer_u\\pycharmprojects\\cyberattacksattention\\venv\\lib\\site-packages (from markdown>=2.6.8->tensorboard<2.12,>=2.11->tensorflow-intel==2.11.0->tensorflow) (5.1.0)\n",
      "Requirement already satisfied: certifi>=2017.4.17 in c:\\users\\fer_u\\pycharmprojects\\cyberattacksattention\\venv\\lib\\site-packages (from requests<3,>=2.21.0->tensorboard<2.12,>=2.11->tensorflow-intel==2.11.0->tensorflow) (2022.12.7)\n",
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      "Requirement already satisfied: urllib3<1.27,>=1.21.1 in c:\\users\\fer_u\\pycharmprojects\\cyberattacksattention\\venv\\lib\\site-packages (from requests<3,>=2.21.0->tensorboard<2.12,>=2.11->tensorflow-intel==2.11.0->tensorflow) (1.26.13)\n",
      "Requirement already satisfied: MarkupSafe>=2.1.1 in c:\\users\\fer_u\\pycharmprojects\\cyberattacksattention\\venv\\lib\\site-packages (from werkzeug>=1.0.1->tensorboard<2.12,>=2.11->tensorflow-intel==2.11.0->tensorflow) (2.1.1)\n",
      "Requirement already satisfied: zipp>=0.5 in c:\\users\\fer_u\\pycharmprojects\\cyberattacksattention\\venv\\lib\\site-packages (from importlib-metadata>=4.4->markdown>=2.6.8->tensorboard<2.12,>=2.11->tensorflow-intel==2.11.0->tensorflow) (3.11.0)\n",
      "Requirement already satisfied: pyasn1<0.5.0,>=0.4.6 in c:\\users\\fer_u\\pycharmprojects\\cyberattacksattention\\venv\\lib\\site-packages (from pyasn1-modules>=0.2.1->google-auth<3,>=1.6.3->tensorboard<2.12,>=2.11->tensorflow-intel==2.11.0->tensorflow) (0.4.8)\n",
      "Requirement already satisfied: oauthlib>=3.0.0 in c:\\users\\fer_u\\pycharmprojects\\cyberattacksattention\\venv\\lib\\site-packages (from requests-oauthlib>=0.7.0->google-auth-oauthlib<0.5,>=0.4.1->tensorboard<2.12,>=2.11->tensorflow-intel==2.11.0->tensorflow) (3.2.2)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING: You are using pip version 21.3.1; however, version 22.3.1 is available.\n",
      "You should consider upgrading via the 'C:\\Users\\Fer_U\\PycharmProjects\\CyberattacksAttention\\venv\\Scripts\\python.exe -m pip install --upgrade pip' command.\n"
     ]
    }
   ],
   "source": [
    "!pip install tensorflow"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: pandas in c:\\users\\fer_u\\pycharmprojects\\cyberattacksattention\\venv\\lib\\site-packages (1.5.2)\n",
      "Requirement already satisfied: numpy>=1.20.3 in c:\\users\\fer_u\\pycharmprojects\\cyberattacksattention\\venv\\lib\\site-packages (from pandas) (1.23.5)\n",
      "Requirement already satisfied: pytz>=2020.1 in c:\\users\\fer_u\\pycharmprojects\\cyberattacksattention\\venv\\lib\\site-packages (from pandas) (2022.6)\n",
      "Requirement already satisfied: python-dateutil>=2.8.1 in c:\\users\\fer_u\\pycharmprojects\\cyberattacksattention\\venv\\lib\\site-packages (from pandas) (2.8.2)\n",
      "Requirement already satisfied: six>=1.5 in c:\\users\\fer_u\\pycharmprojects\\cyberattacksattention\\venv\\lib\\site-packages (from python-dateutil>=2.8.1->pandas) (1.16.0)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING: You are using pip version 21.3.1; however, version 22.3.1 is available.\n",
      "You should consider upgrading via the 'C:\\Users\\Fer_U\\PycharmProjects\\CyberattacksAttention\\venv\\Scripts\\python.exe -m pip install --upgrade pip' command.\n"
     ]
    }
   ],
   "source": [
    "!pip install pandas"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: neural_structured_learning in c:\\users\\fer_u\\pycharmprojects\\cyberattacksattention\\venv\\lib\\site-packages (1.4.0)\n",
      "Requirement already satisfied: attrs in c:\\users\\fer_u\\pycharmprojects\\cyberattacksattention\\venv\\lib\\site-packages (from neural_structured_learning) (22.1.0)\n",
      "Requirement already satisfied: scipy in c:\\users\\fer_u\\pycharmprojects\\cyberattacksattention\\venv\\lib\\site-packages (from neural_structured_learning) (1.9.3)\n",
      "Requirement already satisfied: absl-py in c:\\users\\fer_u\\pycharmprojects\\cyberattacksattention\\venv\\lib\\site-packages (from neural_structured_learning) (1.3.0)\n",
      "Requirement already satisfied: six in c:\\users\\fer_u\\pycharmprojects\\cyberattacksattention\\venv\\lib\\site-packages (from neural_structured_learning) (1.16.0)\n",
      "Requirement already satisfied: numpy<1.26.0,>=1.18.5 in c:\\users\\fer_u\\pycharmprojects\\cyberattacksattention\\venv\\lib\\site-packages (from scipy->neural_structured_learning) (1.23.5)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING: You are using pip version 21.3.1; however, version 22.3.1 is available.\n",
      "You should consider upgrading via the 'C:\\Users\\Fer_U\\PycharmProjects\\CyberattacksAttention\\venv\\Scripts\\python.exe -m pip install --upgrade pip' command.\n"
     ]
    }
   ],
   "source": [
    "!pip install neural_structured_learning"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: scikit_learn in c:\\users\\fer_u\\pycharmprojects\\cyberattacksattention\\venv\\lib\\site-packages (1.2.0)\n",
      "Requirement already satisfied: threadpoolctl>=2.0.0 in c:\\users\\fer_u\\pycharmprojects\\cyberattacksattention\\venv\\lib\\site-packages (from scikit_learn) (3.1.0)\n",
      "Requirement already satisfied: scipy>=1.3.2 in c:\\users\\fer_u\\pycharmprojects\\cyberattacksattention\\venv\\lib\\site-packages (from scikit_learn) (1.9.3)\n",
      "Requirement already satisfied: joblib>=1.1.1 in c:\\users\\fer_u\\pycharmprojects\\cyberattacksattention\\venv\\lib\\site-packages (from scikit_learn) (1.2.0)\n",
      "Requirement already satisfied: numpy>=1.17.3 in c:\\users\\fer_u\\pycharmprojects\\cyberattacksattention\\venv\\lib\\site-packages (from scikit_learn) (1.23.5)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING: You are using pip version 21.3.1; however, version 22.3.1 is available.\n",
      "You should consider upgrading via the 'C:\\Users\\Fer_U\\PycharmProjects\\CyberattacksAttention\\venv\\Scripts\\python.exe -m pip install --upgrade pip' command.\n"
     ]
    }
   ],
   "source": [
    "!pip install scikit_learn"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "executionInfo": {
     "elapsed": 4460,
     "status": "ok",
     "timestamp": 1670604423667,
     "user": {
      "displayName": "Fernando José Rendón Segador",
      "userId": "09288482551460164544"
     },
     "user_tz": -60
    },
    "id": "bTL3Ufo0t487",
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "import tensorflow as tf\n",
    "import pandas as pd\n",
    "import neural_structured_learning as nsl\n",
    "from sklearn.preprocessing import LabelEncoder\n",
    "from sklearn import preprocessing\n",
    "from sklearn.model_selection import *"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "executionInfo": {
     "elapsed": 1214,
     "status": "ok",
     "timestamp": 1670604426852,
     "user": {
      "displayName": "Fernando José Rendón Segador",
      "userId": "09288482551460164544"
     },
     "user_tz": -60
    },
    "id": "xdB9GixktNz0",
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "df = pd.read_csv('ICSX_URL_2017/Phishing.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 300
    },
    "executionInfo": {
     "elapsed": 14,
     "status": "ok",
     "timestamp": 1670604426856,
     "user": {
      "displayName": "Fernando José Rendón Segador",
      "userId": "09288482551460164544"
     },
     "user_tz": -60
    },
    "id": "856UWFEmyUms",
    "outputId": "a5a2bcaf-4a37-454e-eb77-2ffe6b9b956f",
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": "   Querylength  domain_token_count  path_token_count  avgdomaintokenlen  \\\n0            0                   2                12                5.5   \n1            0                   3                12                5.0   \n2            2                   2                11                4.0   \n3            0                   2                 7                4.5   \n4           19                   2                10                6.0   \n\n   longdomaintokenlen  avgpathtokenlen  tld  charcompvowels  charcompace  \\\n0                   8         4.083334    2              15            7   \n1                  10         3.583333    3              12            8   \n2                   5         4.750000    2              16           11   \n3                   7         5.714286    2              15           10   \n4                   9         2.250000    2               9            5   \n\n   ldl_url  ...  SymbolCount_FileName  SymbolCount_Extension  \\\n0        0  ...                    -1                     -1   \n1        2  ...                     1                      0   \n2        0  ...                     2                      0   \n3        0  ...                     0                      0   \n4        0  ...                     5                      4   \n\n   SymbolCount_Afterpath  Entropy_URL  Entropy_Domain  Entropy_DirectoryName  \\\n0                     -1     0.676804        0.860529              -1.000000   \n1                     -1     0.715629        0.776796               0.693127   \n2                      1     0.677701        1.000000               0.677704   \n3                     -1     0.696067        0.879588               0.818007   \n4                      3     0.747202        0.833700               0.655459   \n\n   Entropy_Filename  Entropy_Extension  Entropy_Afterpath  URL_Type_obf_Type  \n0         -1.000000           -1.00000          -1.000000             benign  \n1          0.738315            1.00000          -1.000000             benign  \n2          0.916667            0.00000           0.898227             benign  \n3          0.753585            0.00000          -1.000000             benign  \n4          0.829535            0.83615           0.823008             benign  \n\n[5 rows x 80 columns]",
      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>Querylength</th>\n      <th>domain_token_count</th>\n      <th>path_token_count</th>\n      <th>avgdomaintokenlen</th>\n      <th>longdomaintokenlen</th>\n      <th>avgpathtokenlen</th>\n      <th>tld</th>\n      <th>charcompvowels</th>\n      <th>charcompace</th>\n      <th>ldl_url</th>\n      <th>...</th>\n      <th>SymbolCount_FileName</th>\n      <th>SymbolCount_Extension</th>\n      <th>SymbolCount_Afterpath</th>\n      <th>Entropy_URL</th>\n      <th>Entropy_Domain</th>\n      <th>Entropy_DirectoryName</th>\n      <th>Entropy_Filename</th>\n      <th>Entropy_Extension</th>\n      <th>Entropy_Afterpath</th>\n      <th>URL_Type_obf_Type</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>0</td>\n      <td>2</td>\n      <td>12</td>\n      <td>5.5</td>\n      <td>8</td>\n      <td>4.083334</td>\n      <td>2</td>\n      <td>15</td>\n      <td>7</td>\n      <td>0</td>\n      <td>...</td>\n      <td>-1</td>\n      <td>-1</td>\n      <td>-1</td>\n      <td>0.676804</td>\n      <td>0.860529</td>\n      <td>-1.000000</td>\n      <td>-1.000000</td>\n      <td>-1.00000</td>\n      <td>-1.000000</td>\n      <td>benign</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>0</td>\n      <td>3</td>\n      <td>12</td>\n      <td>5.0</td>\n      <td>10</td>\n      <td>3.583333</td>\n      <td>3</td>\n      <td>12</td>\n      <td>8</td>\n      <td>2</td>\n      <td>...</td>\n      <td>1</td>\n      <td>0</td>\n      <td>-1</td>\n      <td>0.715629</td>\n      <td>0.776796</td>\n      <td>0.693127</td>\n      <td>0.738315</td>\n      <td>1.00000</td>\n      <td>-1.000000</td>\n      <td>benign</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>2</td>\n      <td>2</td>\n      <td>11</td>\n      <td>4.0</td>\n      <td>5</td>\n      <td>4.750000</td>\n      <td>2</td>\n      <td>16</td>\n      <td>11</td>\n      <td>0</td>\n      <td>...</td>\n      <td>2</td>\n      <td>0</td>\n      <td>1</td>\n      <td>0.677701</td>\n      <td>1.000000</td>\n      <td>0.677704</td>\n      <td>0.916667</td>\n      <td>0.00000</td>\n      <td>0.898227</td>\n      <td>benign</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>0</td>\n      <td>2</td>\n      <td>7</td>\n      <td>4.5</td>\n      <td>7</td>\n      <td>5.714286</td>\n      <td>2</td>\n      <td>15</td>\n      <td>10</td>\n      <td>0</td>\n      <td>...</td>\n      <td>0</td>\n      <td>0</td>\n      <td>-1</td>\n      <td>0.696067</td>\n      <td>0.879588</td>\n      <td>0.818007</td>\n      <td>0.753585</td>\n      <td>0.00000</td>\n      <td>-1.000000</td>\n      <td>benign</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>19</td>\n      <td>2</td>\n      <td>10</td>\n      <td>6.0</td>\n      <td>9</td>\n      <td>2.250000</td>\n      <td>2</td>\n      <td>9</td>\n      <td>5</td>\n      <td>0</td>\n      <td>...</td>\n      <td>5</td>\n      <td>4</td>\n      <td>3</td>\n      <td>0.747202</td>\n      <td>0.833700</td>\n      <td>0.655459</td>\n      <td>0.829535</td>\n      <td>0.83615</td>\n      <td>0.823008</td>\n      <td>benign</td>\n    </tr>\n  </tbody>\n</table>\n<p>5 rows × 80 columns</p>\n</div>"
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "executionInfo": {
     "elapsed": 9,
     "status": "ok",
     "timestamp": 1670604426856,
     "user": {
      "displayName": "Fernando José Rendón Segador",
      "userId": "09288482551460164544"
     },
     "user_tz": -60
    },
    "id": "mkez4dRDyZ4L",
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "features = len(df.columns) - 1\n",
    "label_encoder = LabelEncoder()\n",
    "df = df.dropna()\n",
    "df = df.reset_index(drop=True)\n",
    "df['URL_Type_obf_Type'] = label_encoder.fit_transform(df['URL_Type_obf_Type'])\n",
    "classes = df['URL_Type_obf_Type'].nunique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 488
    },
    "executionInfo": {
     "elapsed": 10,
     "status": "ok",
     "timestamp": 1670604426857,
     "user": {
      "displayName": "Fernando José Rendón Segador",
      "userId": "09288482551460164544"
     },
     "user_tz": -60
    },
    "id": "6wz-53mHnm7p",
    "outputId": "fe64ae3c-8710-4fbe-fc93-ff39924faffd",
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": "      Querylength  domain_token_count  path_token_count  avgdomaintokenlen  \\\n0               0                   2                12           5.500000   \n1               0                   3                12           5.000000   \n2              19                   2                10           6.000000   \n3               0                   2                10           5.500000   \n4               0                   2                 9           2.500000   \n...           ...                 ...               ...                ...   \n6718            0                   2                 5           5.500000   \n6719            0                   2                 5           3.500000   \n6720            0                   2                 4           7.000000   \n6721            0                   3                 5           4.666666   \n6722            0                   2                 4           8.000000   \n\n      longdomaintokenlen  avgpathtokenlen  tld  charcompvowels  charcompace  \\\n0                      8         4.083334    2              15            7   \n1                     10         3.583333    3              12            8   \n2                      9         2.250000    2               9            5   \n3                      9         4.100000    2              15           11   \n4                      3         4.555555    2               6            3   \n...                  ...              ...  ...             ...          ...   \n6718                   8         2.800000    2               5            1   \n6719                   5         3.600000    2               5            2   \n6720                  12         3.000000    2               4            2   \n6721                  10         2.000000    3               3            2   \n6722                  13         2.500000    2               1            0   \n\n      ldl_url  ...  SymbolCount_FileName  SymbolCount_Extension  \\\n0           0  ...                    -1                     -1   \n1           2  ...                     1                      0   \n2           0  ...                     5                      4   \n3           0  ...                    -1                     -1   \n4           0  ...                     1                      0   \n...       ...  ...                   ...                    ...   \n6718        0  ...                     1                      0   \n6719        0  ...                     1                      0   \n6720        0  ...                     1                      0   \n6721        0  ...                     1                      0   \n6722        0  ...                     1                      0   \n\n      SymbolCount_Afterpath  Entropy_URL  Entropy_Domain  \\\n0                        -1     0.676804        0.860529   \n1                        -1     0.715629        0.776796   \n2                         3     0.747202        0.833700   \n3                        -1     0.732981        0.860529   \n4                        -1     0.742606        1.000000   \n...                     ...          ...             ...   \n6718                     -1     0.734789        0.953510   \n6719                     -1     0.793129        0.916667   \n6720                     -1     0.797564        0.918863   \n6721                     -1     0.758084        0.906250   \n6722                     -1     0.759976        0.856088   \n\n      Entropy_DirectoryName  Entropy_Filename  Entropy_Extension  \\\n0                 -1.000000         -1.000000           -1.00000   \n1                  0.693127          0.738315            1.00000   \n2                  0.655459          0.829535            0.83615   \n3                 -1.000000         -1.000000           -1.00000   \n4                  0.785719          0.808833            1.00000   \n...                     ...               ...                ...   \n6718               0.693127          1.000000            1.00000   \n6719               0.859582          1.000000            1.00000   \n6720               0.871049          1.000000            1.00000   \n6721               0.833333          1.000000            1.00000   \n6722               0.871049          0.898227            0.57938   \n\n      Entropy_Afterpath  URL_Type_obf_Type  \n0             -1.000000                  0  \n1             -1.000000                  0  \n2              0.823008                  0  \n3             -1.000000                  0  \n4             -1.000000                  0  \n...                 ...                ...  \n6718          -1.000000                  1  \n6719          -1.000000                  1  \n6720          -1.000000                  1  \n6721          -1.000000                  1  \n6722          -1.000000                  1  \n\n[6723 rows x 80 columns]",
      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>Querylength</th>\n      <th>domain_token_count</th>\n      <th>path_token_count</th>\n      <th>avgdomaintokenlen</th>\n      <th>longdomaintokenlen</th>\n      <th>avgpathtokenlen</th>\n      <th>tld</th>\n      <th>charcompvowels</th>\n      <th>charcompace</th>\n      <th>ldl_url</th>\n      <th>...</th>\n      <th>SymbolCount_FileName</th>\n      <th>SymbolCount_Extension</th>\n      <th>SymbolCount_Afterpath</th>\n      <th>Entropy_URL</th>\n      <th>Entropy_Domain</th>\n      <th>Entropy_DirectoryName</th>\n      <th>Entropy_Filename</th>\n      <th>Entropy_Extension</th>\n      <th>Entropy_Afterpath</th>\n      <th>URL_Type_obf_Type</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>0</td>\n      <td>2</td>\n      <td>12</td>\n      <td>5.500000</td>\n      <td>8</td>\n      <td>4.083334</td>\n      <td>2</td>\n      <td>15</td>\n      <td>7</td>\n      <td>0</td>\n      <td>...</td>\n      <td>-1</td>\n      <td>-1</td>\n      <td>-1</td>\n      <td>0.676804</td>\n      <td>0.860529</td>\n      <td>-1.000000</td>\n      <td>-1.000000</td>\n      <td>-1.00000</td>\n      <td>-1.000000</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>0</td>\n      <td>3</td>\n      <td>12</td>\n      <td>5.000000</td>\n      <td>10</td>\n      <td>3.583333</td>\n      <td>3</td>\n      <td>12</td>\n      <td>8</td>\n      <td>2</td>\n      <td>...</td>\n      <td>1</td>\n      <td>0</td>\n      <td>-1</td>\n      <td>0.715629</td>\n      <td>0.776796</td>\n      <td>0.693127</td>\n      <td>0.738315</td>\n      <td>1.00000</td>\n      <td>-1.000000</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>19</td>\n      <td>2</td>\n      <td>10</td>\n      <td>6.000000</td>\n      <td>9</td>\n      <td>2.250000</td>\n      <td>2</td>\n      <td>9</td>\n      <td>5</td>\n      <td>0</td>\n      <td>...</td>\n      <td>5</td>\n      <td>4</td>\n      <td>3</td>\n      <td>0.747202</td>\n      <td>0.833700</td>\n      <td>0.655459</td>\n      <td>0.829535</td>\n      <td>0.83615</td>\n      <td>0.823008</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>0</td>\n      <td>2</td>\n      <td>10</td>\n      <td>5.500000</td>\n      <td>9</td>\n      <td>4.100000</td>\n      <td>2</td>\n      <td>15</td>\n      <td>11</td>\n      <td>0</td>\n      <td>...</td>\n      <td>-1</td>\n      <td>-1</td>\n      <td>-1</td>\n      <td>0.732981</td>\n      <td>0.860529</td>\n      <td>-1.000000</td>\n      <td>-1.000000</td>\n      <td>-1.00000</td>\n      <td>-1.000000</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>0</td>\n      <td>2</td>\n      <td>9</td>\n      <td>2.500000</td>\n      <td>3</td>\n      <td>4.555555</td>\n      <td>2</td>\n      <td>6</td>\n      <td>3</td>\n      <td>0</td>\n      <td>...</td>\n      <td>1</td>\n      <td>0</td>\n      <td>-1</td>\n      <td>0.742606</td>\n      <td>1.000000</td>\n      <td>0.785719</td>\n      <td>0.808833</td>\n      <td>1.00000</td>\n      <td>-1.000000</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>...</th>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n    </tr>\n    <tr>\n      <th>6718</th>\n      <td>0</td>\n      <td>2</td>\n      <td>5</td>\n      <td>5.500000</td>\n      <td>8</td>\n      <td>2.800000</td>\n      <td>2</td>\n      <td>5</td>\n      <td>1</td>\n      <td>0</td>\n      <td>...</td>\n      <td>1</td>\n      <td>0</td>\n      <td>-1</td>\n      <td>0.734789</td>\n      <td>0.953510</td>\n      <td>0.693127</td>\n      <td>1.000000</td>\n      <td>1.00000</td>\n      <td>-1.000000</td>\n      <td>1</td>\n    </tr>\n    <tr>\n      <th>6719</th>\n      <td>0</td>\n      <td>2</td>\n      <td>5</td>\n      <td>3.500000</td>\n      <td>5</td>\n      <td>3.600000</td>\n      <td>2</td>\n      <td>5</td>\n      <td>2</td>\n      <td>0</td>\n      <td>...</td>\n      <td>1</td>\n      <td>0</td>\n      <td>-1</td>\n      <td>0.793129</td>\n      <td>0.916667</td>\n      <td>0.859582</td>\n      <td>1.000000</td>\n      <td>1.00000</td>\n      <td>-1.000000</td>\n      <td>1</td>\n    </tr>\n    <tr>\n      <th>6720</th>\n      <td>0</td>\n      <td>2</td>\n      <td>4</td>\n      <td>7.000000</td>\n      <td>12</td>\n      <td>3.000000</td>\n      <td>2</td>\n      <td>4</td>\n      <td>2</td>\n      <td>0</td>\n      <td>...</td>\n      <td>1</td>\n      <td>0</td>\n      <td>-1</td>\n      <td>0.797564</td>\n      <td>0.918863</td>\n      <td>0.871049</td>\n      <td>1.000000</td>\n      <td>1.00000</td>\n      <td>-1.000000</td>\n      <td>1</td>\n    </tr>\n    <tr>\n      <th>6721</th>\n      <td>0</td>\n      <td>3</td>\n      <td>5</td>\n      <td>4.666666</td>\n      <td>10</td>\n      <td>2.000000</td>\n      <td>3</td>\n      <td>3</td>\n      <td>2</td>\n      <td>0</td>\n      <td>...</td>\n      <td>1</td>\n      <td>0</td>\n      <td>-1</td>\n      <td>0.758084</td>\n      <td>0.906250</td>\n      <td>0.833333</td>\n      <td>1.000000</td>\n      <td>1.00000</td>\n      <td>-1.000000</td>\n      <td>1</td>\n    </tr>\n    <tr>\n      <th>6722</th>\n      <td>0</td>\n      <td>2</td>\n      <td>4</td>\n      <td>8.000000</td>\n      <td>13</td>\n      <td>2.500000</td>\n      <td>2</td>\n      <td>1</td>\n      <td>0</td>\n      <td>0</td>\n      <td>...</td>\n      <td>1</td>\n      <td>0</td>\n      <td>-1</td>\n      <td>0.759976</td>\n      <td>0.856088</td>\n      <td>0.871049</td>\n      <td>0.898227</td>\n      <td>0.57938</td>\n      <td>-1.000000</td>\n      <td>1</td>\n    </tr>\n  </tbody>\n</table>\n<p>6723 rows × 80 columns</p>\n</div>"
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 331
    },
    "executionInfo": {
     "elapsed": 9,
     "status": "ok",
     "timestamp": 1670604426857,
     "user": {
      "displayName": "Fernando José Rendón Segador",
      "userId": "09288482551460164544"
     },
     "user_tz": -60
    },
    "id": "pDdBjmOgVZdA",
    "outputId": "649a90de-aad7-4207-a533-07f3a793c1d5",
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": "                   Querylength  domain_token_count  path_token_count  \\\nURL_Type_obf_Type                                                      \n0                         2709                2709              2709   \n1                         4014                4014              4014   \n\n                   avgdomaintokenlen  longdomaintokenlen  avgpathtokenlen  \\\nURL_Type_obf_Type                                                           \n0                               2709                2709             2709   \n1                               4014                4014             4014   \n\n                    tld  charcompvowels  charcompace  ldl_url  ...  \\\nURL_Type_obf_Type                                              ...   \n0                  2709            2709         2709     2709  ...   \n1                  4014            4014         4014     4014  ...   \n\n                   SymbolCount_Directoryname  SymbolCount_FileName  \\\nURL_Type_obf_Type                                                    \n0                                       2709                  2709   \n1                                       4014                  4014   \n\n                   SymbolCount_Extension  SymbolCount_Afterpath  Entropy_URL  \\\nURL_Type_obf_Type                                                              \n0                                   2709                   2709         2709   \n1                                   4014                   4014         4014   \n\n                   Entropy_Domain  Entropy_DirectoryName  Entropy_Filename  \\\nURL_Type_obf_Type                                                            \n0                            2709                   2709              2709   \n1                            4014                   4014              4014   \n\n                   Entropy_Extension  Entropy_Afterpath  \nURL_Type_obf_Type                                        \n0                               2709               2709  \n1                               4014               4014  \n\n[2 rows x 79 columns]",
      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>Querylength</th>\n      <th>domain_token_count</th>\n      <th>path_token_count</th>\n      <th>avgdomaintokenlen</th>\n      <th>longdomaintokenlen</th>\n      <th>avgpathtokenlen</th>\n      <th>tld</th>\n      <th>charcompvowels</th>\n      <th>charcompace</th>\n      <th>ldl_url</th>\n      <th>...</th>\n      <th>SymbolCount_Directoryname</th>\n      <th>SymbolCount_FileName</th>\n      <th>SymbolCount_Extension</th>\n      <th>SymbolCount_Afterpath</th>\n      <th>Entropy_URL</th>\n      <th>Entropy_Domain</th>\n      <th>Entropy_DirectoryName</th>\n      <th>Entropy_Filename</th>\n      <th>Entropy_Extension</th>\n      <th>Entropy_Afterpath</th>\n    </tr>\n    <tr>\n      <th>URL_Type_obf_Type</th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>2709</td>\n      <td>2709</td>\n      <td>2709</td>\n      <td>2709</td>\n      <td>2709</td>\n      <td>2709</td>\n      <td>2709</td>\n      <td>2709</td>\n      <td>2709</td>\n      <td>2709</td>\n      <td>...</td>\n      <td>2709</td>\n      <td>2709</td>\n      <td>2709</td>\n      <td>2709</td>\n      <td>2709</td>\n      <td>2709</td>\n      <td>2709</td>\n      <td>2709</td>\n      <td>2709</td>\n      <td>2709</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>4014</td>\n      <td>4014</td>\n      <td>4014</td>\n      <td>4014</td>\n      <td>4014</td>\n      <td>4014</td>\n      <td>4014</td>\n      <td>4014</td>\n      <td>4014</td>\n      <td>4014</td>\n      <td>...</td>\n      <td>4014</td>\n      <td>4014</td>\n      <td>4014</td>\n      <td>4014</td>\n      <td>4014</td>\n      <td>4014</td>\n      <td>4014</td>\n      <td>4014</td>\n      <td>4014</td>\n      <td>4014</td>\n    </tr>\n  </tbody>\n</table>\n<p>2 rows × 79 columns</p>\n</div>"
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.groupby('URL_Type_obf_Type').count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "executionInfo": {
     "elapsed": 8,
     "status": "ok",
     "timestamp": 1670604426857,
     "user": {
      "displayName": "Fernando José Rendón Segador",
      "userId": "09288482551460164544"
     },
     "user_tz": -60
    },
    "id": "5MKUhTHEVvn8",
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "df_0 = df.loc[df['URL_Type_obf_Type'] == 0]\n",
    "df_1 = df.loc[df['URL_Type_obf_Type'] == 1]\n",
    "df_2 = df.loc[df['URL_Type_obf_Type'] == 2]\n",
    "df_3 = df.loc[df['URL_Type_obf_Type'] == 3]\n",
    "df_4 = df.loc[df['URL_Type_obf_Type'] == 4]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 488
    },
    "executionInfo": {
     "elapsed": 413,
     "status": "ok",
     "timestamp": 1670604427263,
     "user": {
      "displayName": "Fernando José Rendón Segador",
      "userId": "09288482551460164544"
     },
     "user_tz": -60
    },
    "id": "VBg_I0QKXFk0",
    "outputId": "761a2fc5-02e5-46f0-eb8a-f7fd4f9bc9a0",
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": "      Querylength  domain_token_count  path_token_count  avgdomaintokenlen  \\\n0               0                   2                12           5.500000   \n1               0                   3                12           5.000000   \n2              19                   2                10           6.000000   \n3               0                   2                10           5.500000   \n4               0                   2                 9           2.500000   \n...           ...                 ...               ...                ...   \n6718            0                   2                 5           5.500000   \n6719            0                   2                 5           3.500000   \n6720            0                   2                 4           7.000000   \n6721            0                   3                 5           4.666666   \n6722            0                   2                 4           8.000000   \n\n      longdomaintokenlen  avgpathtokenlen  tld  charcompvowels  charcompace  \\\n0                      8         4.083334    2              15            7   \n1                     10         3.583333    3              12            8   \n2                      9         2.250000    2               9            5   \n3                      9         4.100000    2              15           11   \n4                      3         4.555555    2               6            3   \n...                  ...              ...  ...             ...          ...   \n6718                   8         2.800000    2               5            1   \n6719                   5         3.600000    2               5            2   \n6720                  12         3.000000    2               4            2   \n6721                  10         2.000000    3               3            2   \n6722                  13         2.500000    2               1            0   \n\n      ldl_url  ...  SymbolCount_FileName  SymbolCount_Extension  \\\n0           0  ...                    -1                     -1   \n1           2  ...                     1                      0   \n2           0  ...                     5                      4   \n3           0  ...                    -1                     -1   \n4           0  ...                     1                      0   \n...       ...  ...                   ...                    ...   \n6718        0  ...                     1                      0   \n6719        0  ...                     1                      0   \n6720        0  ...                     1                      0   \n6721        0  ...                     1                      0   \n6722        0  ...                     1                      0   \n\n      SymbolCount_Afterpath  Entropy_URL  Entropy_Domain  \\\n0                        -1     0.676804        0.860529   \n1                        -1     0.715629        0.776796   \n2                         3     0.747202        0.833700   \n3                        -1     0.732981        0.860529   \n4                        -1     0.742606        1.000000   \n...                     ...          ...             ...   \n6718                     -1     0.734789        0.953510   \n6719                     -1     0.793129        0.916667   \n6720                     -1     0.797564        0.918863   \n6721                     -1     0.758084        0.906250   \n6722                     -1     0.759976        0.856088   \n\n      Entropy_DirectoryName  Entropy_Filename  Entropy_Extension  \\\n0                 -1.000000         -1.000000           -1.00000   \n1                  0.693127          0.738315            1.00000   \n2                  0.655459          0.829535            0.83615   \n3                 -1.000000         -1.000000           -1.00000   \n4                  0.785719          0.808833            1.00000   \n...                     ...               ...                ...   \n6718               0.693127          1.000000            1.00000   \n6719               0.859582          1.000000            1.00000   \n6720               0.871049          1.000000            1.00000   \n6721               0.833333          1.000000            1.00000   \n6722               0.871049          0.898227            0.57938   \n\n      Entropy_Afterpath  URL_Type_obf_Type  \n0             -1.000000                  0  \n1             -1.000000                  0  \n2              0.823008                  0  \n3             -1.000000                  0  \n4             -1.000000                  0  \n...                 ...                ...  \n6718          -1.000000                  1  \n6719          -1.000000                  1  \n6720          -1.000000                  1  \n6721          -1.000000                  1  \n6722          -1.000000                  1  \n\n[6723 rows x 80 columns]",
      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>Querylength</th>\n      <th>domain_token_count</th>\n      <th>path_token_count</th>\n      <th>avgdomaintokenlen</th>\n      <th>longdomaintokenlen</th>\n      <th>avgpathtokenlen</th>\n      <th>tld</th>\n      <th>charcompvowels</th>\n      <th>charcompace</th>\n      <th>ldl_url</th>\n      <th>...</th>\n      <th>SymbolCount_FileName</th>\n      <th>SymbolCount_Extension</th>\n      <th>SymbolCount_Afterpath</th>\n      <th>Entropy_URL</th>\n      <th>Entropy_Domain</th>\n      <th>Entropy_DirectoryName</th>\n      <th>Entropy_Filename</th>\n      <th>Entropy_Extension</th>\n      <th>Entropy_Afterpath</th>\n      <th>URL_Type_obf_Type</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>0</td>\n      <td>2</td>\n      <td>12</td>\n      <td>5.500000</td>\n      <td>8</td>\n      <td>4.083334</td>\n      <td>2</td>\n      <td>15</td>\n      <td>7</td>\n      <td>0</td>\n      <td>...</td>\n      <td>-1</td>\n      <td>-1</td>\n      <td>-1</td>\n      <td>0.676804</td>\n      <td>0.860529</td>\n      <td>-1.000000</td>\n      <td>-1.000000</td>\n      <td>-1.00000</td>\n      <td>-1.000000</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>0</td>\n      <td>3</td>\n      <td>12</td>\n      <td>5.000000</td>\n      <td>10</td>\n      <td>3.583333</td>\n      <td>3</td>\n      <td>12</td>\n      <td>8</td>\n      <td>2</td>\n      <td>...</td>\n      <td>1</td>\n      <td>0</td>\n      <td>-1</td>\n      <td>0.715629</td>\n      <td>0.776796</td>\n      <td>0.693127</td>\n      <td>0.738315</td>\n      <td>1.00000</td>\n      <td>-1.000000</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>19</td>\n      <td>2</td>\n      <td>10</td>\n      <td>6.000000</td>\n      <td>9</td>\n      <td>2.250000</td>\n      <td>2</td>\n      <td>9</td>\n      <td>5</td>\n      <td>0</td>\n      <td>...</td>\n      <td>5</td>\n      <td>4</td>\n      <td>3</td>\n      <td>0.747202</td>\n      <td>0.833700</td>\n      <td>0.655459</td>\n      <td>0.829535</td>\n      <td>0.83615</td>\n      <td>0.823008</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>0</td>\n      <td>2</td>\n      <td>10</td>\n      <td>5.500000</td>\n      <td>9</td>\n      <td>4.100000</td>\n      <td>2</td>\n      <td>15</td>\n      <td>11</td>\n      <td>0</td>\n      <td>...</td>\n      <td>-1</td>\n      <td>-1</td>\n      <td>-1</td>\n      <td>0.732981</td>\n      <td>0.860529</td>\n      <td>-1.000000</td>\n      <td>-1.000000</td>\n      <td>-1.00000</td>\n      <td>-1.000000</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>0</td>\n      <td>2</td>\n      <td>9</td>\n      <td>2.500000</td>\n      <td>3</td>\n      <td>4.555555</td>\n      <td>2</td>\n      <td>6</td>\n      <td>3</td>\n      <td>0</td>\n      <td>...</td>\n      <td>1</td>\n      <td>0</td>\n      <td>-1</td>\n      <td>0.742606</td>\n      <td>1.000000</td>\n      <td>0.785719</td>\n      <td>0.808833</td>\n      <td>1.00000</td>\n      <td>-1.000000</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>...</th>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n    </tr>\n    <tr>\n      <th>6718</th>\n      <td>0</td>\n      <td>2</td>\n      <td>5</td>\n      <td>5.500000</td>\n      <td>8</td>\n      <td>2.800000</td>\n      <td>2</td>\n      <td>5</td>\n      <td>1</td>\n      <td>0</td>\n      <td>...</td>\n      <td>1</td>\n      <td>0</td>\n      <td>-1</td>\n      <td>0.734789</td>\n      <td>0.953510</td>\n      <td>0.693127</td>\n      <td>1.000000</td>\n      <td>1.00000</td>\n      <td>-1.000000</td>\n      <td>1</td>\n    </tr>\n    <tr>\n      <th>6719</th>\n      <td>0</td>\n      <td>2</td>\n      <td>5</td>\n      <td>3.500000</td>\n      <td>5</td>\n      <td>3.600000</td>\n      <td>2</td>\n      <td>5</td>\n      <td>2</td>\n      <td>0</td>\n      <td>...</td>\n      <td>1</td>\n      <td>0</td>\n      <td>-1</td>\n      <td>0.793129</td>\n      <td>0.916667</td>\n      <td>0.859582</td>\n      <td>1.000000</td>\n      <td>1.00000</td>\n      <td>-1.000000</td>\n      <td>1</td>\n    </tr>\n    <tr>\n      <th>6720</th>\n      <td>0</td>\n      <td>2</td>\n      <td>4</td>\n      <td>7.000000</td>\n      <td>12</td>\n      <td>3.000000</td>\n      <td>2</td>\n      <td>4</td>\n      <td>2</td>\n      <td>0</td>\n      <td>...</td>\n      <td>1</td>\n      <td>0</td>\n      <td>-1</td>\n      <td>0.797564</td>\n      <td>0.918863</td>\n      <td>0.871049</td>\n      <td>1.000000</td>\n      <td>1.00000</td>\n      <td>-1.000000</td>\n      <td>1</td>\n    </tr>\n    <tr>\n      <th>6721</th>\n      <td>0</td>\n      <td>3</td>\n      <td>5</td>\n      <td>4.666666</td>\n      <td>10</td>\n      <td>2.000000</td>\n      <td>3</td>\n      <td>3</td>\n      <td>2</td>\n      <td>0</td>\n      <td>...</td>\n      <td>1</td>\n      <td>0</td>\n      <td>-1</td>\n      <td>0.758084</td>\n      <td>0.906250</td>\n      <td>0.833333</td>\n      <td>1.000000</td>\n      <td>1.00000</td>\n      <td>-1.000000</td>\n      <td>1</td>\n    </tr>\n    <tr>\n      <th>6722</th>\n      <td>0</td>\n      <td>2</td>\n      <td>4</td>\n      <td>8.000000</td>\n      <td>13</td>\n      <td>2.500000</td>\n      <td>2</td>\n      <td>1</td>\n      <td>0</td>\n      <td>0</td>\n      <td>...</td>\n      <td>1</td>\n      <td>0</td>\n      <td>-1</td>\n      <td>0.759976</td>\n      <td>0.856088</td>\n      <td>0.871049</td>\n      <td>0.898227</td>\n      <td>0.57938</td>\n      <td>-1.000000</td>\n      <td>1</td>\n    </tr>\n  </tbody>\n</table>\n<p>6723 rows × 80 columns</p>\n</div>"
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.concat([df_0, df_1, df_2, df_3, df_4])\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "executionInfo": {
     "elapsed": 4,
     "status": "ok",
     "timestamp": 1670604427264,
     "user": {
      "displayName": "Fernando José Rendón Segador",
      "userId": "09288482551460164544"
     },
     "user_tz": -60
    },
    "id": "9s_HaYjkzuKk",
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "y = df.pop('URL_Type_obf_Type')\n",
    "X = df\n",
    "\n",
    "normalizer_scaler = preprocessing.Normalizer()\n",
    "x_scaled = normalizer_scaler.fit_transform(X)\n",
    "X = pd.DataFrame(x_scaled)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "executionInfo": {
     "elapsed": 4,
     "status": "ok",
     "timestamp": 1670604427264,
     "user": {
      "displayName": "Fernando José Rendón Segador",
      "userId": "09288482551460164544"
     },
     "user_tz": -60
    },
    "id": "l-9LdOome2ck",
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.20, random_state=42)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "executionInfo": {
     "elapsed": 3,
     "status": "ok",
     "timestamp": 1670604427264,
     "user": {
      "displayName": "Fernando José Rendón Segador",
      "userId": "09288482551460164544"
     },
     "user_tz": -60
    },
    "id": "FC6lXk4Az3yB",
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "X_train = tf.convert_to_tensor(X_train)\n",
    "y_train = tf.convert_to_tensor(y_train)\n",
    "\n",
    "X_test = tf.convert_to_tensor(X_test)\n",
    "y_test = tf.convert_to_tensor(y_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "executionInfo": {
     "elapsed": 333,
     "status": "ok",
     "timestamp": 1670604427594,
     "user": {
      "displayName": "Fernando José Rendón Segador",
      "userId": "09288482551460164544"
     },
     "user_tz": -60
    },
    "id": "SP8ckOayytne",
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "input = tf.keras.layers.Input((features,), name='feature')\n",
    "\n",
    "n1 = tf.keras.layers.Dense(32)(input)\n",
    "n1 = tf.keras.layers.Dropout(0.25)(n1)\n",
    "n1 = tf.keras.layers.Dense(64)(n1)\n",
    "n1 = tf.keras.layers.Dropout(0.25)(n1)\n",
    "n1 = tf.keras.layers.Dense(128)(n1)\n",
    "n1 = tf.keras.layers.Dropout(0.25)(n1)\n",
    "n1 = tf.keras.layers.Dense(256)(n1)\n",
    "\n",
    "n1 = tf.keras.layers.MultiHeadAttention(num_heads=int(256/8), key_dim=256, value_dim=256, attention_axes=1)(n1, n1, n1)\n",
    "\n",
    "n1 = tf.keras.layers.Dense(256)(n1)\n",
    "n1 = tf.keras.layers.Dropout(0.25)(n1)\n",
    "n1 = tf.keras.layers.Dense(128)(n1)\n",
    "n1 = tf.keras.layers.Dropout(0.25)(n1)\n",
    "n1 = tf.keras.layers.Dense(64)(n1)\n",
    "n1 = tf.keras.layers.Dropout(0.25)(n1)\n",
    "n1 = tf.keras.layers.Dense(32)(n1)\n",
    "\n",
    "output = tf.keras.layers.Dense(classes, activation='softmax')(n1)\n",
    "\n",
    "model = tf.keras.Model(inputs=input, outputs=output)\n",
    "\n",
    "adv_config = nsl.configs.make_adv_reg_config(multiplier=0.2, adv_step_size=0.05)\n",
    "adv_model = nsl.keras.AdversarialRegularization(model, adv_config=adv_config)\n",
    "\n",
    "# Compile, train, and evaluate.\n",
    "adv_model.compile(optimizer='adam',\n",
    "                  loss='sparse_categorical_crossentropy',\n",
    "                  metrics=['accuracy'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "executionInfo": {
     "elapsed": 269,
     "status": "ok",
     "timestamp": 1670604427855,
     "user": {
      "displayName": "Fernando José Rendón Segador",
      "userId": "09288482551460164544"
     },
     "user_tz": -60
    },
    "id": "-EUxz4vRy7YP",
    "outputId": "1c8c1a81-6e6b-4129-f8a2-9d22f904cb87",
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model: \"model_1\"\n",
      "__________________________________________________________________________________________________\n",
      " Layer (type)                   Output Shape         Param #     Connected to                     \n",
      "==================================================================================================\n",
      " feature (InputLayer)           [(None, 79)]         0           []                               \n",
      "                                                                                                  \n",
      " dense_9 (Dense)                (None, 32)           2560        ['feature[0][0]']                \n",
      "                                                                                                  \n",
      " dropout_6 (Dropout)            (None, 32)           0           ['dense_9[0][0]']                \n",
      "                                                                                                  \n",
      " dense_10 (Dense)               (None, 64)           2112        ['dropout_6[0][0]']              \n",
      "                                                                                                  \n",
      " dropout_7 (Dropout)            (None, 64)           0           ['dense_10[0][0]']               \n",
      "                                                                                                  \n",
      " dense_11 (Dense)               (None, 128)          8320        ['dropout_7[0][0]']              \n",
      "                                                                                                  \n",
      " dropout_8 (Dropout)            (None, 128)          0           ['dense_11[0][0]']               \n",
      "                                                                                                  \n",
      " dense_12 (Dense)               (None, 256)          33024       ['dropout_8[0][0]']              \n",
      "                                                                                                  \n",
      " multi_head_attention_1 (MultiH  (None, 256)         8413440     ['dense_12[0][0]',               \n",
      " eadAttention)                                                    'dense_12[0][0]',               \n",
      "                                                                  'dense_12[0][0]']               \n",
      "                                                                                                  \n",
      " dense_13 (Dense)               (None, 256)          65792       ['multi_head_attention_1[0][0]'] \n",
      "                                                                                                  \n",
      " dropout_9 (Dropout)            (None, 256)          0           ['dense_13[0][0]']               \n",
      "                                                                                                  \n",
      " dense_14 (Dense)               (None, 128)          32896       ['dropout_9[0][0]']              \n",
      "                                                                                                  \n",
      " dropout_10 (Dropout)           (None, 128)          0           ['dense_14[0][0]']               \n",
      "                                                                                                  \n",
      " dense_15 (Dense)               (None, 64)           8256        ['dropout_10[0][0]']             \n",
      "                                                                                                  \n",
      " dropout_11 (Dropout)           (None, 64)           0           ['dense_15[0][0]']               \n",
      "                                                                                                  \n",
      " dense_16 (Dense)               (None, 32)           2080        ['dropout_11[0][0]']             \n",
      "                                                                                                  \n",
      " dense_17 (Dense)               (None, 2)            66          ['dense_16[0][0]']               \n",
      "                                                                                                  \n",
      "==================================================================================================\n",
      "Total params: 8,568,546\n",
      "Trainable params: 8,568,546\n",
      "Non-trainable params: 0\n",
      "__________________________________________________________________________________________________\n"
     ]
    }
   ],
   "source": [
    "model.summary()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 48
    },
    "executionInfo": {
     "elapsed": 447,
     "status": "ok",
     "timestamp": 1670604428298,
     "user": {
      "displayName": "Fernando José Rendón Segador",
      "userId": "09288482551460164544"
     },
     "user_tz": -60
    },
    "id": "844W7YPn82Gw",
    "outputId": "ea88bcec-2ee8-4229-e43f-6c1a767fdc89",
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "You must install pydot (`pip install pydot`) and install graphviz (see instructions at https://graphviz.gitlab.io/download/) for plot_model to work.\n"
     ]
    }
   ],
   "source": [
    "tf.keras.utils.plot_model(model, \n",
    "                          show_shapes=True,\n",
    "                          show_dtype=True,\n",
    "                          show_layer_names=True,\n",
    "                          rankdir='LR')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "RjM9Xf2Ry-lq",
    "outputId": "3f4f80c6-a5ac-4e5e-8981-be5081cd7e3c",
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/1000\n",
      "11/11 [==============================] - 6s 366ms/step - loss: 0.8049 - sparse_categorical_crossentropy: 0.6504 - sparse_categorical_accuracy: 0.6575 - scaled_adversarial_loss: 0.1545 - val_loss: 0.6313 - val_sparse_categorical_crossentropy: 0.4886 - val_sparse_categorical_accuracy: 0.7383 - val_scaled_adversarial_loss: 0.1427\n",
      "Epoch 2/1000\n",
      "11/11 [==============================] - 4s 335ms/step - loss: 0.6099 - sparse_categorical_crossentropy: 0.4727 - sparse_categorical_accuracy: 0.7733 - scaled_adversarial_loss: 0.1372 - val_loss: 0.5351 - val_sparse_categorical_crossentropy: 0.3873 - val_sparse_categorical_accuracy: 0.8327 - val_scaled_adversarial_loss: 0.1478\n",
      "Epoch 3/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.5441 - sparse_categorical_crossentropy: 0.4077 - sparse_categorical_accuracy: 0.8178 - scaled_adversarial_loss: 0.1364 - val_loss: 0.4875 - val_sparse_categorical_crossentropy: 0.3505 - val_sparse_categorical_accuracy: 0.8342 - val_scaled_adversarial_loss: 0.1370\n",
      "Epoch 4/1000\n",
      "11/11 [==============================] - 4s 342ms/step - loss: 0.5033 - sparse_categorical_crossentropy: 0.3711 - sparse_categorical_accuracy: 0.8353 - scaled_adversarial_loss: 0.1322 - val_loss: 0.4567 - val_sparse_categorical_crossentropy: 0.3157 - val_sparse_categorical_accuracy: 0.8610 - val_scaled_adversarial_loss: 0.1410\n",
      "Epoch 5/1000\n",
      "11/11 [==============================] - 4s 336ms/step - loss: 0.4706 - sparse_categorical_crossentropy: 0.3366 - sparse_categorical_accuracy: 0.8578 - scaled_adversarial_loss: 0.1340 - val_loss: 0.4436 - val_sparse_categorical_crossentropy: 0.3051 - val_sparse_categorical_accuracy: 0.8773 - val_scaled_adversarial_loss: 0.1385\n",
      "Epoch 6/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.4618 - sparse_categorical_crossentropy: 0.3270 - sparse_categorical_accuracy: 0.8721 - scaled_adversarial_loss: 0.1348 - val_loss: 0.4309 - val_sparse_categorical_crossentropy: 0.2878 - val_sparse_categorical_accuracy: 0.8818 - val_scaled_adversarial_loss: 0.1431\n",
      "Epoch 7/1000\n",
      "11/11 [==============================] - 4s 336ms/step - loss: 0.4449 - sparse_categorical_crossentropy: 0.3109 - sparse_categorical_accuracy: 0.8762 - scaled_adversarial_loss: 0.1340 - val_loss: 0.4260 - val_sparse_categorical_crossentropy: 0.2857 - val_sparse_categorical_accuracy: 0.8967 - val_scaled_adversarial_loss: 0.1403\n",
      "Epoch 8/1000\n",
      "11/11 [==============================] - 4s 335ms/step - loss: 0.4369 - sparse_categorical_crossentropy: 0.3008 - sparse_categorical_accuracy: 0.8814 - scaled_adversarial_loss: 0.1361 - val_loss: 0.4209 - val_sparse_categorical_crossentropy: 0.2786 - val_sparse_categorical_accuracy: 0.8959 - val_scaled_adversarial_loss: 0.1423\n",
      "Epoch 9/1000\n",
      "11/11 [==============================] - 4s 337ms/step - loss: 0.4343 - sparse_categorical_crossentropy: 0.2954 - sparse_categorical_accuracy: 0.8836 - scaled_adversarial_loss: 0.1390 - val_loss: 0.4314 - val_sparse_categorical_crossentropy: 0.2830 - val_sparse_categorical_accuracy: 0.8743 - val_scaled_adversarial_loss: 0.1484\n",
      "Epoch 10/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.4177 - sparse_categorical_crossentropy: 0.2777 - sparse_categorical_accuracy: 0.8925 - scaled_adversarial_loss: 0.1400 - val_loss: 0.4143 - val_sparse_categorical_crossentropy: 0.2657 - val_sparse_categorical_accuracy: 0.8952 - val_scaled_adversarial_loss: 0.1486\n",
      "Epoch 11/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.4181 - sparse_categorical_crossentropy: 0.2780 - sparse_categorical_accuracy: 0.8948 - scaled_adversarial_loss: 0.1401 - val_loss: 0.4064 - val_sparse_categorical_crossentropy: 0.2496 - val_sparse_categorical_accuracy: 0.8989 - val_scaled_adversarial_loss: 0.1568\n",
      "Epoch 12/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.4120 - sparse_categorical_crossentropy: 0.2669 - sparse_categorical_accuracy: 0.8992 - scaled_adversarial_loss: 0.1451 - val_loss: 0.4086 - val_sparse_categorical_crossentropy: 0.2421 - val_sparse_categorical_accuracy: 0.9019 - val_scaled_adversarial_loss: 0.1665\n",
      "Epoch 13/1000\n",
      "11/11 [==============================] - 4s 337ms/step - loss: 0.4162 - sparse_categorical_crossentropy: 0.2703 - sparse_categorical_accuracy: 0.9024 - scaled_adversarial_loss: 0.1459 - val_loss: 0.4056 - val_sparse_categorical_crossentropy: 0.2559 - val_sparse_categorical_accuracy: 0.9011 - val_scaled_adversarial_loss: 0.1497\n",
      "Epoch 14/1000\n",
      "11/11 [==============================] - 4s 336ms/step - loss: 0.4106 - sparse_categorical_crossentropy: 0.2669 - sparse_categorical_accuracy: 0.9011 - scaled_adversarial_loss: 0.1436 - val_loss: 0.4039 - val_sparse_categorical_crossentropy: 0.2344 - val_sparse_categorical_accuracy: 0.9019 - val_scaled_adversarial_loss: 0.1696\n",
      "Epoch 15/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.4075 - sparse_categorical_crossentropy: 0.2618 - sparse_categorical_accuracy: 0.8996 - scaled_adversarial_loss: 0.1457 - val_loss: 0.4065 - val_sparse_categorical_crossentropy: 0.2586 - val_sparse_categorical_accuracy: 0.9004 - val_scaled_adversarial_loss: 0.1479\n",
      "Epoch 16/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.4084 - sparse_categorical_crossentropy: 0.2637 - sparse_categorical_accuracy: 0.8981 - scaled_adversarial_loss: 0.1448 - val_loss: 0.3991 - val_sparse_categorical_crossentropy: 0.2373 - val_sparse_categorical_accuracy: 0.9108 - val_scaled_adversarial_loss: 0.1617\n",
      "Epoch 17/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.4068 - sparse_categorical_crossentropy: 0.2626 - sparse_categorical_accuracy: 0.8974 - scaled_adversarial_loss: 0.1442 - val_loss: 0.4050 - val_sparse_categorical_crossentropy: 0.2448 - val_sparse_categorical_accuracy: 0.9041 - val_scaled_adversarial_loss: 0.1602\n",
      "Epoch 18/1000\n",
      "11/11 [==============================] - 4s 332ms/step - loss: 0.4085 - sparse_categorical_crossentropy: 0.2669 - sparse_categorical_accuracy: 0.8957 - scaled_adversarial_loss: 0.1416 - val_loss: 0.4149 - val_sparse_categorical_crossentropy: 0.2327 - val_sparse_categorical_accuracy: 0.9152 - val_scaled_adversarial_loss: 0.1822\n",
      "Epoch 19/1000\n",
      "11/11 [==============================] - 4s 332ms/step - loss: 0.4057 - sparse_categorical_crossentropy: 0.2603 - sparse_categorical_accuracy: 0.8977 - scaled_adversarial_loss: 0.1454 - val_loss: 0.4129 - val_sparse_categorical_crossentropy: 0.2334 - val_sparse_categorical_accuracy: 0.9086 - val_scaled_adversarial_loss: 0.1795\n",
      "Epoch 20/1000\n",
      "11/11 [==============================] - 4s 345ms/step - loss: 0.4139 - sparse_categorical_crossentropy: 0.2652 - sparse_categorical_accuracy: 0.9015 - scaled_adversarial_loss: 0.1487 - val_loss: 0.4119 - val_sparse_categorical_crossentropy: 0.2685 - val_sparse_categorical_accuracy: 0.9011 - val_scaled_adversarial_loss: 0.1434\n",
      "Epoch 21/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.4041 - sparse_categorical_crossentropy: 0.2591 - sparse_categorical_accuracy: 0.9015 - scaled_adversarial_loss: 0.1450 - val_loss: 0.3988 - val_sparse_categorical_crossentropy: 0.2346 - val_sparse_categorical_accuracy: 0.9011 - val_scaled_adversarial_loss: 0.1641\n",
      "Epoch 22/1000\n",
      "11/11 [==============================] - 4s 331ms/step - loss: 0.4098 - sparse_categorical_crossentropy: 0.2607 - sparse_categorical_accuracy: 0.9033 - scaled_adversarial_loss: 0.1491 - val_loss: 0.4022 - val_sparse_categorical_crossentropy: 0.2335 - val_sparse_categorical_accuracy: 0.9004 - val_scaled_adversarial_loss: 0.1687\n",
      "Epoch 23/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.4050 - sparse_categorical_crossentropy: 0.2545 - sparse_categorical_accuracy: 0.9067 - scaled_adversarial_loss: 0.1506 - val_loss: 0.4133 - val_sparse_categorical_crossentropy: 0.2684 - val_sparse_categorical_accuracy: 0.9078 - val_scaled_adversarial_loss: 0.1450\n",
      "Epoch 24/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.4040 - sparse_categorical_crossentropy: 0.2577 - sparse_categorical_accuracy: 0.9041 - scaled_adversarial_loss: 0.1463 - val_loss: 0.3961 - val_sparse_categorical_crossentropy: 0.2377 - val_sparse_categorical_accuracy: 0.9093 - val_scaled_adversarial_loss: 0.1584\n",
      "Epoch 25/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.3997 - sparse_categorical_crossentropy: 0.2541 - sparse_categorical_accuracy: 0.9031 - scaled_adversarial_loss: 0.1456 - val_loss: 0.3969 - val_sparse_categorical_crossentropy: 0.2354 - val_sparse_categorical_accuracy: 0.9145 - val_scaled_adversarial_loss: 0.1615\n",
      "Epoch 26/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.3969 - sparse_categorical_crossentropy: 0.2485 - sparse_categorical_accuracy: 0.9052 - scaled_adversarial_loss: 0.1484 - val_loss: 0.4031 - val_sparse_categorical_crossentropy: 0.2470 - val_sparse_categorical_accuracy: 0.9130 - val_scaled_adversarial_loss: 0.1561\n",
      "Epoch 27/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.3999 - sparse_categorical_crossentropy: 0.2545 - sparse_categorical_accuracy: 0.9013 - scaled_adversarial_loss: 0.1454 - val_loss: 0.3950 - val_sparse_categorical_crossentropy: 0.2343 - val_sparse_categorical_accuracy: 0.9100 - val_scaled_adversarial_loss: 0.1606\n",
      "Epoch 28/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.3976 - sparse_categorical_crossentropy: 0.2508 - sparse_categorical_accuracy: 0.9054 - scaled_adversarial_loss: 0.1468 - val_loss: 0.3972 - val_sparse_categorical_crossentropy: 0.2417 - val_sparse_categorical_accuracy: 0.9048 - val_scaled_adversarial_loss: 0.1555\n",
      "Epoch 29/1000\n",
      "11/11 [==============================] - 4s 332ms/step - loss: 0.3994 - sparse_categorical_crossentropy: 0.2539 - sparse_categorical_accuracy: 0.9028 - scaled_adversarial_loss: 0.1455 - val_loss: 0.3971 - val_sparse_categorical_crossentropy: 0.2399 - val_sparse_categorical_accuracy: 0.9048 - val_scaled_adversarial_loss: 0.1573\n",
      "Epoch 30/1000\n",
      "11/11 [==============================] - 4s 331ms/step - loss: 0.4028 - sparse_categorical_crossentropy: 0.2531 - sparse_categorical_accuracy: 0.9028 - scaled_adversarial_loss: 0.1497 - val_loss: 0.3987 - val_sparse_categorical_crossentropy: 0.2267 - val_sparse_categorical_accuracy: 0.9048 - val_scaled_adversarial_loss: 0.1720\n",
      "Epoch 31/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.3960 - sparse_categorical_crossentropy: 0.2476 - sparse_categorical_accuracy: 0.9074 - scaled_adversarial_loss: 0.1484 - val_loss: 0.4021 - val_sparse_categorical_crossentropy: 0.2500 - val_sparse_categorical_accuracy: 0.8996 - val_scaled_adversarial_loss: 0.1521\n",
      "Epoch 32/1000\n",
      "11/11 [==============================] - 4s 332ms/step - loss: 0.3940 - sparse_categorical_crossentropy: 0.2483 - sparse_categorical_accuracy: 0.9089 - scaled_adversarial_loss: 0.1457 - val_loss: 0.3978 - val_sparse_categorical_crossentropy: 0.2423 - val_sparse_categorical_accuracy: 0.9011 - val_scaled_adversarial_loss: 0.1555\n",
      "Epoch 33/1000\n",
      "11/11 [==============================] - 4s 332ms/step - loss: 0.4021 - sparse_categorical_crossentropy: 0.2529 - sparse_categorical_accuracy: 0.9048 - scaled_adversarial_loss: 0.1492 - val_loss: 0.3933 - val_sparse_categorical_crossentropy: 0.2328 - val_sparse_categorical_accuracy: 0.9063 - val_scaled_adversarial_loss: 0.1605\n",
      "Epoch 34/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.3947 - sparse_categorical_crossentropy: 0.2479 - sparse_categorical_accuracy: 0.9078 - scaled_adversarial_loss: 0.1468 - val_loss: 0.3951 - val_sparse_categorical_crossentropy: 0.2292 - val_sparse_categorical_accuracy: 0.9063 - val_scaled_adversarial_loss: 0.1659\n",
      "Epoch 35/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.4021 - sparse_categorical_crossentropy: 0.2511 - sparse_categorical_accuracy: 0.9068 - scaled_adversarial_loss: 0.1510 - val_loss: 0.3945 - val_sparse_categorical_crossentropy: 0.2339 - val_sparse_categorical_accuracy: 0.9048 - val_scaled_adversarial_loss: 0.1606\n",
      "Epoch 36/1000\n",
      "11/11 [==============================] - 4s 337ms/step - loss: 0.3940 - sparse_categorical_crossentropy: 0.2470 - sparse_categorical_accuracy: 0.9068 - scaled_adversarial_loss: 0.1470 - val_loss: 0.3997 - val_sparse_categorical_crossentropy: 0.2451 - val_sparse_categorical_accuracy: 0.9004 - val_scaled_adversarial_loss: 0.1546\n",
      "Epoch 37/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.3915 - sparse_categorical_crossentropy: 0.2444 - sparse_categorical_accuracy: 0.9055 - scaled_adversarial_loss: 0.1472 - val_loss: 0.3940 - val_sparse_categorical_crossentropy: 0.2379 - val_sparse_categorical_accuracy: 0.9063 - val_scaled_adversarial_loss: 0.1561\n",
      "Epoch 38/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.3975 - sparse_categorical_crossentropy: 0.2497 - sparse_categorical_accuracy: 0.9054 - scaled_adversarial_loss: 0.1479 - val_loss: 0.3945 - val_sparse_categorical_crossentropy: 0.2308 - val_sparse_categorical_accuracy: 0.9056 - val_scaled_adversarial_loss: 0.1636\n",
      "Epoch 39/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.3956 - sparse_categorical_crossentropy: 0.2481 - sparse_categorical_accuracy: 0.9054 - scaled_adversarial_loss: 0.1475 - val_loss: 0.3929 - val_sparse_categorical_crossentropy: 0.2273 - val_sparse_categorical_accuracy: 0.9115 - val_scaled_adversarial_loss: 0.1656\n",
      "Epoch 40/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.3969 - sparse_categorical_crossentropy: 0.2481 - sparse_categorical_accuracy: 0.9050 - scaled_adversarial_loss: 0.1488 - val_loss: 0.4023 - val_sparse_categorical_crossentropy: 0.2342 - val_sparse_categorical_accuracy: 0.9138 - val_scaled_adversarial_loss: 0.1681\n",
      "Epoch 41/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.3988 - sparse_categorical_crossentropy: 0.2510 - sparse_categorical_accuracy: 0.9041 - scaled_adversarial_loss: 0.1478 - val_loss: 0.3952 - val_sparse_categorical_crossentropy: 0.2431 - val_sparse_categorical_accuracy: 0.9048 - val_scaled_adversarial_loss: 0.1521\n",
      "Epoch 42/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.3918 - sparse_categorical_crossentropy: 0.2447 - sparse_categorical_accuracy: 0.9087 - scaled_adversarial_loss: 0.1471 - val_loss: 0.3969 - val_sparse_categorical_crossentropy: 0.2263 - val_sparse_categorical_accuracy: 0.9063 - val_scaled_adversarial_loss: 0.1706\n",
      "Epoch 43/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.3906 - sparse_categorical_crossentropy: 0.2438 - sparse_categorical_accuracy: 0.9093 - scaled_adversarial_loss: 0.1468 - val_loss: 0.4053 - val_sparse_categorical_crossentropy: 0.2411 - val_sparse_categorical_accuracy: 0.8959 - val_scaled_adversarial_loss: 0.1643\n",
      "Epoch 44/1000\n",
      "11/11 [==============================] - 4s 332ms/step - loss: 0.3925 - sparse_categorical_crossentropy: 0.2461 - sparse_categorical_accuracy: 0.9089 - scaled_adversarial_loss: 0.1463 - val_loss: 0.3933 - val_sparse_categorical_crossentropy: 0.2332 - val_sparse_categorical_accuracy: 0.9063 - val_scaled_adversarial_loss: 0.1601\n",
      "Epoch 45/1000\n",
      "11/11 [==============================] - 4s 339ms/step - loss: 0.3957 - sparse_categorical_crossentropy: 0.2455 - sparse_categorical_accuracy: 0.9063 - scaled_adversarial_loss: 0.1502 - val_loss: 0.3984 - val_sparse_categorical_crossentropy: 0.2495 - val_sparse_categorical_accuracy: 0.9041 - val_scaled_adversarial_loss: 0.1489\n",
      "Epoch 46/1000\n",
      "11/11 [==============================] - 4s 331ms/step - loss: 0.3972 - sparse_categorical_crossentropy: 0.2485 - sparse_categorical_accuracy: 0.9078 - scaled_adversarial_loss: 0.1486 - val_loss: 0.4008 - val_sparse_categorical_crossentropy: 0.2473 - val_sparse_categorical_accuracy: 0.9152 - val_scaled_adversarial_loss: 0.1535\n",
      "Epoch 47/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.3952 - sparse_categorical_crossentropy: 0.2488 - sparse_categorical_accuracy: 0.9067 - scaled_adversarial_loss: 0.1464 - val_loss: 0.3947 - val_sparse_categorical_crossentropy: 0.2313 - val_sparse_categorical_accuracy: 0.9033 - val_scaled_adversarial_loss: 0.1634\n",
      "Epoch 48/1000\n",
      "11/11 [==============================] - 4s 336ms/step - loss: 0.3934 - sparse_categorical_crossentropy: 0.2452 - sparse_categorical_accuracy: 0.9046 - scaled_adversarial_loss: 0.1482 - val_loss: 0.3956 - val_sparse_categorical_crossentropy: 0.2394 - val_sparse_categorical_accuracy: 0.9138 - val_scaled_adversarial_loss: 0.1562\n",
      "Epoch 49/1000\n",
      "11/11 [==============================] - 4s 339ms/step - loss: 0.3947 - sparse_categorical_crossentropy: 0.2494 - sparse_categorical_accuracy: 0.9081 - scaled_adversarial_loss: 0.1453 - val_loss: 0.3926 - val_sparse_categorical_crossentropy: 0.2300 - val_sparse_categorical_accuracy: 0.9115 - val_scaled_adversarial_loss: 0.1627\n",
      "Epoch 50/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.3941 - sparse_categorical_crossentropy: 0.2439 - sparse_categorical_accuracy: 0.9070 - scaled_adversarial_loss: 0.1501 - val_loss: 0.4100 - val_sparse_categorical_crossentropy: 0.2667 - val_sparse_categorical_accuracy: 0.9048 - val_scaled_adversarial_loss: 0.1433\n",
      "Epoch 51/1000\n",
      "11/11 [==============================] - 4s 346ms/step - loss: 0.3990 - sparse_categorical_crossentropy: 0.2503 - sparse_categorical_accuracy: 0.9093 - scaled_adversarial_loss: 0.1487 - val_loss: 0.3970 - val_sparse_categorical_crossentropy: 0.2208 - val_sparse_categorical_accuracy: 0.9130 - val_scaled_adversarial_loss: 0.1763\n",
      "Epoch 52/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.4003 - sparse_categorical_crossentropy: 0.2459 - sparse_categorical_accuracy: 0.9093 - scaled_adversarial_loss: 0.1544 - val_loss: 0.3999 - val_sparse_categorical_crossentropy: 0.2475 - val_sparse_categorical_accuracy: 0.8981 - val_scaled_adversarial_loss: 0.1524\n",
      "Epoch 53/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.4014 - sparse_categorical_crossentropy: 0.2560 - sparse_categorical_accuracy: 0.9068 - scaled_adversarial_loss: 0.1455 - val_loss: 0.4049 - val_sparse_categorical_crossentropy: 0.2591 - val_sparse_categorical_accuracy: 0.9048 - val_scaled_adversarial_loss: 0.1458\n",
      "Epoch 54/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.3982 - sparse_categorical_crossentropy: 0.2500 - sparse_categorical_accuracy: 0.9080 - scaled_adversarial_loss: 0.1481 - val_loss: 0.3921 - val_sparse_categorical_crossentropy: 0.2319 - val_sparse_categorical_accuracy: 0.9063 - val_scaled_adversarial_loss: 0.1602\n",
      "Epoch 55/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.3950 - sparse_categorical_crossentropy: 0.2443 - sparse_categorical_accuracy: 0.9054 - scaled_adversarial_loss: 0.1507 - val_loss: 0.3935 - val_sparse_categorical_crossentropy: 0.2317 - val_sparse_categorical_accuracy: 0.9063 - val_scaled_adversarial_loss: 0.1618\n",
      "Epoch 56/1000\n",
      "11/11 [==============================] - 4s 345ms/step - loss: 0.3892 - sparse_categorical_crossentropy: 0.2414 - sparse_categorical_accuracy: 0.9081 - scaled_adversarial_loss: 0.1478 - val_loss: 0.3936 - val_sparse_categorical_crossentropy: 0.2297 - val_sparse_categorical_accuracy: 0.9138 - val_scaled_adversarial_loss: 0.1639\n",
      "Epoch 57/1000\n",
      "11/11 [==============================] - 4s 371ms/step - loss: 0.3939 - sparse_categorical_crossentropy: 0.2437 - sparse_categorical_accuracy: 0.9087 - scaled_adversarial_loss: 0.1503 - val_loss: 0.4025 - val_sparse_categorical_crossentropy: 0.2571 - val_sparse_categorical_accuracy: 0.9056 - val_scaled_adversarial_loss: 0.1455\n",
      "Epoch 58/1000\n",
      "11/11 [==============================] - 4s 338ms/step - loss: 0.3952 - sparse_categorical_crossentropy: 0.2497 - sparse_categorical_accuracy: 0.9091 - scaled_adversarial_loss: 0.1454 - val_loss: 0.3919 - val_sparse_categorical_crossentropy: 0.2275 - val_sparse_categorical_accuracy: 0.9130 - val_scaled_adversarial_loss: 0.1644\n",
      "Epoch 59/1000\n",
      "11/11 [==============================] - 4s 341ms/step - loss: 0.3933 - sparse_categorical_crossentropy: 0.2412 - sparse_categorical_accuracy: 0.9093 - scaled_adversarial_loss: 0.1521 - val_loss: 0.3936 - val_sparse_categorical_crossentropy: 0.2362 - val_sparse_categorical_accuracy: 0.9056 - val_scaled_adversarial_loss: 0.1574\n",
      "Epoch 60/1000\n",
      "11/11 [==============================] - 4s 351ms/step - loss: 0.3930 - sparse_categorical_crossentropy: 0.2435 - sparse_categorical_accuracy: 0.9098 - scaled_adversarial_loss: 0.1495 - val_loss: 0.3954 - val_sparse_categorical_crossentropy: 0.2276 - val_sparse_categorical_accuracy: 0.9033 - val_scaled_adversarial_loss: 0.1677\n",
      "Epoch 61/1000\n",
      "11/11 [==============================] - 4s 342ms/step - loss: 0.3928 - sparse_categorical_crossentropy: 0.2441 - sparse_categorical_accuracy: 0.9096 - scaled_adversarial_loss: 0.1487 - val_loss: 0.4052 - val_sparse_categorical_crossentropy: 0.2366 - val_sparse_categorical_accuracy: 0.8952 - val_scaled_adversarial_loss: 0.1686\n",
      "Epoch 62/1000\n",
      "11/11 [==============================] - 4s 339ms/step - loss: 0.3935 - sparse_categorical_crossentropy: 0.2451 - sparse_categorical_accuracy: 0.9076 - scaled_adversarial_loss: 0.1484 - val_loss: 0.4048 - val_sparse_categorical_crossentropy: 0.2475 - val_sparse_categorical_accuracy: 0.8914 - val_scaled_adversarial_loss: 0.1573\n",
      "Epoch 63/1000\n",
      "11/11 [==============================] - 4s 340ms/step - loss: 0.3922 - sparse_categorical_crossentropy: 0.2468 - sparse_categorical_accuracy: 0.9065 - scaled_adversarial_loss: 0.1454 - val_loss: 0.4002 - val_sparse_categorical_crossentropy: 0.2471 - val_sparse_categorical_accuracy: 0.8967 - val_scaled_adversarial_loss: 0.1531\n",
      "Epoch 64/1000\n",
      "11/11 [==============================] - 4s 347ms/step - loss: 0.3974 - sparse_categorical_crossentropy: 0.2464 - sparse_categorical_accuracy: 0.9087 - scaled_adversarial_loss: 0.1510 - val_loss: 0.4010 - val_sparse_categorical_crossentropy: 0.2429 - val_sparse_categorical_accuracy: 0.8944 - val_scaled_adversarial_loss: 0.1580\n",
      "Epoch 65/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.3949 - sparse_categorical_crossentropy: 0.2469 - sparse_categorical_accuracy: 0.9055 - scaled_adversarial_loss: 0.1480 - val_loss: 0.4073 - val_sparse_categorical_crossentropy: 0.2504 - val_sparse_categorical_accuracy: 0.8907 - val_scaled_adversarial_loss: 0.1569\n",
      "Epoch 66/1000\n",
      "11/11 [==============================] - 4s 339ms/step - loss: 0.3881 - sparse_categorical_crossentropy: 0.2406 - sparse_categorical_accuracy: 0.9096 - scaled_adversarial_loss: 0.1475 - val_loss: 0.3960 - val_sparse_categorical_crossentropy: 0.2431 - val_sparse_categorical_accuracy: 0.9041 - val_scaled_adversarial_loss: 0.1529\n",
      "Epoch 67/1000\n",
      "11/11 [==============================] - 4s 338ms/step - loss: 0.3934 - sparse_categorical_crossentropy: 0.2451 - sparse_categorical_accuracy: 0.9078 - scaled_adversarial_loss: 0.1483 - val_loss: 0.3960 - val_sparse_categorical_crossentropy: 0.2388 - val_sparse_categorical_accuracy: 0.9019 - val_scaled_adversarial_loss: 0.1573\n",
      "Epoch 68/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.3946 - sparse_categorical_crossentropy: 0.2473 - sparse_categorical_accuracy: 0.9055 - scaled_adversarial_loss: 0.1474 - val_loss: 0.3940 - val_sparse_categorical_crossentropy: 0.2404 - val_sparse_categorical_accuracy: 0.9056 - val_scaled_adversarial_loss: 0.1536\n",
      "Epoch 69/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.3899 - sparse_categorical_crossentropy: 0.2429 - sparse_categorical_accuracy: 0.9083 - scaled_adversarial_loss: 0.1470 - val_loss: 0.3939 - val_sparse_categorical_crossentropy: 0.2279 - val_sparse_categorical_accuracy: 0.9048 - val_scaled_adversarial_loss: 0.1660\n",
      "Epoch 70/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.3959 - sparse_categorical_crossentropy: 0.2418 - sparse_categorical_accuracy: 0.9089 - scaled_adversarial_loss: 0.1541 - val_loss: 0.3975 - val_sparse_categorical_crossentropy: 0.2229 - val_sparse_categorical_accuracy: 0.9078 - val_scaled_adversarial_loss: 0.1746\n",
      "Epoch 71/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.4011 - sparse_categorical_crossentropy: 0.2522 - sparse_categorical_accuracy: 0.9074 - scaled_adversarial_loss: 0.1488 - val_loss: 0.4142 - val_sparse_categorical_crossentropy: 0.2731 - val_sparse_categorical_accuracy: 0.8967 - val_scaled_adversarial_loss: 0.1411\n",
      "Epoch 72/1000\n",
      "11/11 [==============================] - 4s 332ms/step - loss: 0.3946 - sparse_categorical_crossentropy: 0.2477 - sparse_categorical_accuracy: 0.9100 - scaled_adversarial_loss: 0.1469 - val_loss: 0.4054 - val_sparse_categorical_crossentropy: 0.2424 - val_sparse_categorical_accuracy: 0.8937 - val_scaled_adversarial_loss: 0.1630\n",
      "Epoch 73/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.3889 - sparse_categorical_crossentropy: 0.2406 - sparse_categorical_accuracy: 0.9100 - scaled_adversarial_loss: 0.1482 - val_loss: 0.4092 - val_sparse_categorical_crossentropy: 0.2383 - val_sparse_categorical_accuracy: 0.8937 - val_scaled_adversarial_loss: 0.1709\n",
      "Epoch 74/1000\n",
      "11/11 [==============================] - 4s 339ms/step - loss: 0.3924 - sparse_categorical_crossentropy: 0.2437 - sparse_categorical_accuracy: 0.9074 - scaled_adversarial_loss: 0.1487 - val_loss: 0.4036 - val_sparse_categorical_crossentropy: 0.2458 - val_sparse_categorical_accuracy: 0.8944 - val_scaled_adversarial_loss: 0.1578\n",
      "Epoch 75/1000\n",
      "11/11 [==============================] - 4s 332ms/step - loss: 0.4009 - sparse_categorical_crossentropy: 0.2518 - sparse_categorical_accuracy: 0.9001 - scaled_adversarial_loss: 0.1491 - val_loss: 0.4045 - val_sparse_categorical_crossentropy: 0.2610 - val_sparse_categorical_accuracy: 0.9056 - val_scaled_adversarial_loss: 0.1435\n",
      "Epoch 76/1000\n",
      "11/11 [==============================] - 4s 339ms/step - loss: 0.3983 - sparse_categorical_crossentropy: 0.2533 - sparse_categorical_accuracy: 0.9074 - scaled_adversarial_loss: 0.1450 - val_loss: 0.4002 - val_sparse_categorical_crossentropy: 0.2538 - val_sparse_categorical_accuracy: 0.9115 - val_scaled_adversarial_loss: 0.1464\n",
      "Epoch 77/1000\n",
      "11/11 [==============================] - 4s 343ms/step - loss: 0.3944 - sparse_categorical_crossentropy: 0.2451 - sparse_categorical_accuracy: 0.9057 - scaled_adversarial_loss: 0.1494 - val_loss: 0.3968 - val_sparse_categorical_crossentropy: 0.2213 - val_sparse_categorical_accuracy: 0.9071 - val_scaled_adversarial_loss: 0.1755\n",
      "Epoch 78/1000\n",
      "11/11 [==============================] - 4s 338ms/step - loss: 0.3903 - sparse_categorical_crossentropy: 0.2394 - sparse_categorical_accuracy: 0.9100 - scaled_adversarial_loss: 0.1509 - val_loss: 0.3911 - val_sparse_categorical_crossentropy: 0.2263 - val_sparse_categorical_accuracy: 0.9100 - val_scaled_adversarial_loss: 0.1648\n",
      "Epoch 79/1000\n",
      "11/11 [==============================] - 4s 343ms/step - loss: 0.3960 - sparse_categorical_crossentropy: 0.2437 - sparse_categorical_accuracy: 0.9122 - scaled_adversarial_loss: 0.1523 - val_loss: 0.3962 - val_sparse_categorical_crossentropy: 0.2461 - val_sparse_categorical_accuracy: 0.9078 - val_scaled_adversarial_loss: 0.1501\n",
      "Epoch 80/1000\n",
      "11/11 [==============================] - 4s 345ms/step - loss: 0.3892 - sparse_categorical_crossentropy: 0.2421 - sparse_categorical_accuracy: 0.9115 - scaled_adversarial_loss: 0.1471 - val_loss: 0.3946 - val_sparse_categorical_crossentropy: 0.2422 - val_sparse_categorical_accuracy: 0.9063 - val_scaled_adversarial_loss: 0.1524\n",
      "Epoch 81/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.3851 - sparse_categorical_crossentropy: 0.2362 - sparse_categorical_accuracy: 0.9113 - scaled_adversarial_loss: 0.1489 - val_loss: 0.3944 - val_sparse_categorical_crossentropy: 0.2394 - val_sparse_categorical_accuracy: 0.9048 - val_scaled_adversarial_loss: 0.1550\n",
      "Epoch 82/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.3884 - sparse_categorical_crossentropy: 0.2393 - sparse_categorical_accuracy: 0.9117 - scaled_adversarial_loss: 0.1491 - val_loss: 0.3948 - val_sparse_categorical_crossentropy: 0.2227 - val_sparse_categorical_accuracy: 0.9093 - val_scaled_adversarial_loss: 0.1722\n",
      "Epoch 83/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.3888 - sparse_categorical_crossentropy: 0.2404 - sparse_categorical_accuracy: 0.9106 - scaled_adversarial_loss: 0.1484 - val_loss: 0.3986 - val_sparse_categorical_crossentropy: 0.2494 - val_sparse_categorical_accuracy: 0.9115 - val_scaled_adversarial_loss: 0.1492\n",
      "Epoch 84/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.3936 - sparse_categorical_crossentropy: 0.2439 - sparse_categorical_accuracy: 0.9098 - scaled_adversarial_loss: 0.1497 - val_loss: 0.4023 - val_sparse_categorical_crossentropy: 0.2563 - val_sparse_categorical_accuracy: 0.9108 - val_scaled_adversarial_loss: 0.1459\n",
      "Epoch 85/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.3923 - sparse_categorical_crossentropy: 0.2428 - sparse_categorical_accuracy: 0.9102 - scaled_adversarial_loss: 0.1495 - val_loss: 0.3920 - val_sparse_categorical_crossentropy: 0.2230 - val_sparse_categorical_accuracy: 0.9093 - val_scaled_adversarial_loss: 0.1690\n",
      "Epoch 86/1000\n",
      "11/11 [==============================] - 4s 332ms/step - loss: 0.3921 - sparse_categorical_crossentropy: 0.2412 - sparse_categorical_accuracy: 0.9080 - scaled_adversarial_loss: 0.1510 - val_loss: 0.3963 - val_sparse_categorical_crossentropy: 0.2273 - val_sparse_categorical_accuracy: 0.9071 - val_scaled_adversarial_loss: 0.1691\n",
      "Epoch 87/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.3937 - sparse_categorical_crossentropy: 0.2434 - sparse_categorical_accuracy: 0.9072 - scaled_adversarial_loss: 0.1503 - val_loss: 0.3940 - val_sparse_categorical_crossentropy: 0.2370 - val_sparse_categorical_accuracy: 0.9063 - val_scaled_adversarial_loss: 0.1569\n",
      "Epoch 88/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.3831 - sparse_categorical_crossentropy: 0.2359 - sparse_categorical_accuracy: 0.9119 - scaled_adversarial_loss: 0.1472 - val_loss: 0.4065 - val_sparse_categorical_crossentropy: 0.2434 - val_sparse_categorical_accuracy: 0.8922 - val_scaled_adversarial_loss: 0.1632\n",
      "Epoch 89/1000\n",
      "11/11 [==============================] - 4s 332ms/step - loss: 0.3920 - sparse_categorical_crossentropy: 0.2437 - sparse_categorical_accuracy: 0.9113 - scaled_adversarial_loss: 0.1484 - val_loss: 0.4000 - val_sparse_categorical_crossentropy: 0.2474 - val_sparse_categorical_accuracy: 0.8952 - val_scaled_adversarial_loss: 0.1526\n",
      "Epoch 90/1000\n",
      "11/11 [==============================] - 4s 332ms/step - loss: 0.3902 - sparse_categorical_crossentropy: 0.2425 - sparse_categorical_accuracy: 0.9085 - scaled_adversarial_loss: 0.1477 - val_loss: 0.3930 - val_sparse_categorical_crossentropy: 0.2333 - val_sparse_categorical_accuracy: 0.9056 - val_scaled_adversarial_loss: 0.1598\n",
      "Epoch 91/1000\n",
      "11/11 [==============================] - 4s 331ms/step - loss: 0.3850 - sparse_categorical_crossentropy: 0.2387 - sparse_categorical_accuracy: 0.9094 - scaled_adversarial_loss: 0.1462 - val_loss: 0.3912 - val_sparse_categorical_crossentropy: 0.2291 - val_sparse_categorical_accuracy: 0.9078 - val_scaled_adversarial_loss: 0.1621\n",
      "Epoch 92/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.3886 - sparse_categorical_crossentropy: 0.2387 - sparse_categorical_accuracy: 0.9096 - scaled_adversarial_loss: 0.1499 - val_loss: 0.3910 - val_sparse_categorical_crossentropy: 0.2315 - val_sparse_categorical_accuracy: 0.9078 - val_scaled_adversarial_loss: 0.1596\n",
      "Epoch 93/1000\n",
      "11/11 [==============================] - 4s 332ms/step - loss: 0.3869 - sparse_categorical_crossentropy: 0.2408 - sparse_categorical_accuracy: 0.9089 - scaled_adversarial_loss: 0.1462 - val_loss: 0.3952 - val_sparse_categorical_crossentropy: 0.2451 - val_sparse_categorical_accuracy: 0.9145 - val_scaled_adversarial_loss: 0.1501\n",
      "Epoch 94/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.3949 - sparse_categorical_crossentropy: 0.2450 - sparse_categorical_accuracy: 0.9093 - scaled_adversarial_loss: 0.1499 - val_loss: 0.3950 - val_sparse_categorical_crossentropy: 0.2240 - val_sparse_categorical_accuracy: 0.9071 - val_scaled_adversarial_loss: 0.1709\n",
      "Epoch 95/1000\n",
      "11/11 [==============================] - 4s 331ms/step - loss: 0.3869 - sparse_categorical_crossentropy: 0.2359 - sparse_categorical_accuracy: 0.9102 - scaled_adversarial_loss: 0.1510 - val_loss: 0.3936 - val_sparse_categorical_crossentropy: 0.2381 - val_sparse_categorical_accuracy: 0.9056 - val_scaled_adversarial_loss: 0.1556\n",
      "Epoch 96/1000\n",
      "11/11 [==============================] - 4s 331ms/step - loss: 0.3915 - sparse_categorical_crossentropy: 0.2460 - sparse_categorical_accuracy: 0.9094 - scaled_adversarial_loss: 0.1455 - val_loss: 0.3912 - val_sparse_categorical_crossentropy: 0.2323 - val_sparse_categorical_accuracy: 0.9071 - val_scaled_adversarial_loss: 0.1590\n",
      "Epoch 97/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.3841 - sparse_categorical_crossentropy: 0.2347 - sparse_categorical_accuracy: 0.9115 - scaled_adversarial_loss: 0.1494 - val_loss: 0.3902 - val_sparse_categorical_crossentropy: 0.2247 - val_sparse_categorical_accuracy: 0.9138 - val_scaled_adversarial_loss: 0.1655\n",
      "Epoch 98/1000\n",
      "11/11 [==============================] - 4s 331ms/step - loss: 0.3843 - sparse_categorical_crossentropy: 0.2392 - sparse_categorical_accuracy: 0.9115 - scaled_adversarial_loss: 0.1452 - val_loss: 0.3977 - val_sparse_categorical_crossentropy: 0.2284 - val_sparse_categorical_accuracy: 0.9048 - val_scaled_adversarial_loss: 0.1693\n",
      "Epoch 99/1000\n",
      "11/11 [==============================] - 4s 332ms/step - loss: 0.3823 - sparse_categorical_crossentropy: 0.2347 - sparse_categorical_accuracy: 0.9137 - scaled_adversarial_loss: 0.1476 - val_loss: 0.3993 - val_sparse_categorical_crossentropy: 0.2226 - val_sparse_categorical_accuracy: 0.9071 - val_scaled_adversarial_loss: 0.1767\n",
      "Epoch 100/1000\n",
      "11/11 [==============================] - 4s 336ms/step - loss: 0.3869 - sparse_categorical_crossentropy: 0.2360 - sparse_categorical_accuracy: 0.9109 - scaled_adversarial_loss: 0.1509 - val_loss: 0.3905 - val_sparse_categorical_crossentropy: 0.2355 - val_sparse_categorical_accuracy: 0.9167 - val_scaled_adversarial_loss: 0.1551\n",
      "Epoch 101/1000\n",
      "11/11 [==============================] - 4s 331ms/step - loss: 0.3809 - sparse_categorical_crossentropy: 0.2333 - sparse_categorical_accuracy: 0.9126 - scaled_adversarial_loss: 0.1475 - val_loss: 0.3894 - val_sparse_categorical_crossentropy: 0.2299 - val_sparse_categorical_accuracy: 0.9160 - val_scaled_adversarial_loss: 0.1595\n",
      "Epoch 102/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.3845 - sparse_categorical_crossentropy: 0.2365 - sparse_categorical_accuracy: 0.9111 - scaled_adversarial_loss: 0.1481 - val_loss: 0.3931 - val_sparse_categorical_crossentropy: 0.2431 - val_sparse_categorical_accuracy: 0.9138 - val_scaled_adversarial_loss: 0.1501\n",
      "Epoch 103/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.3788 - sparse_categorical_crossentropy: 0.2325 - sparse_categorical_accuracy: 0.9124 - scaled_adversarial_loss: 0.1463 - val_loss: 0.3936 - val_sparse_categorical_crossentropy: 0.2197 - val_sparse_categorical_accuracy: 0.9123 - val_scaled_adversarial_loss: 0.1739\n",
      "Epoch 104/1000\n",
      "11/11 [==============================] - 4s 330ms/step - loss: 0.3845 - sparse_categorical_crossentropy: 0.2337 - sparse_categorical_accuracy: 0.9094 - scaled_adversarial_loss: 0.1507 - val_loss: 0.3898 - val_sparse_categorical_crossentropy: 0.2342 - val_sparse_categorical_accuracy: 0.9115 - val_scaled_adversarial_loss: 0.1557\n",
      "Epoch 105/1000\n",
      "11/11 [==============================] - 4s 332ms/step - loss: 0.3891 - sparse_categorical_crossentropy: 0.2418 - sparse_categorical_accuracy: 0.9107 - scaled_adversarial_loss: 0.1473 - val_loss: 0.3918 - val_sparse_categorical_crossentropy: 0.2374 - val_sparse_categorical_accuracy: 0.9071 - val_scaled_adversarial_loss: 0.1544\n",
      "Epoch 106/1000\n",
      "11/11 [==============================] - 4s 332ms/step - loss: 0.3849 - sparse_categorical_crossentropy: 0.2378 - sparse_categorical_accuracy: 0.9115 - scaled_adversarial_loss: 0.1471 - val_loss: 0.3960 - val_sparse_categorical_crossentropy: 0.2265 - val_sparse_categorical_accuracy: 0.9100 - val_scaled_adversarial_loss: 0.1695\n",
      "Epoch 107/1000\n",
      "11/11 [==============================] - 4s 331ms/step - loss: 0.3882 - sparse_categorical_crossentropy: 0.2371 - sparse_categorical_accuracy: 0.9128 - scaled_adversarial_loss: 0.1511 - val_loss: 0.3906 - val_sparse_categorical_crossentropy: 0.2386 - val_sparse_categorical_accuracy: 0.9093 - val_scaled_adversarial_loss: 0.1520\n",
      "Epoch 108/1000\n",
      "11/11 [==============================] - 4s 331ms/step - loss: 0.3876 - sparse_categorical_crossentropy: 0.2415 - sparse_categorical_accuracy: 0.9128 - scaled_adversarial_loss: 0.1461 - val_loss: 0.3882 - val_sparse_categorical_crossentropy: 0.2273 - val_sparse_categorical_accuracy: 0.9086 - val_scaled_adversarial_loss: 0.1608\n",
      "Epoch 109/1000\n",
      "11/11 [==============================] - 4s 332ms/step - loss: 0.3841 - sparse_categorical_crossentropy: 0.2369 - sparse_categorical_accuracy: 0.9111 - scaled_adversarial_loss: 0.1472 - val_loss: 0.3939 - val_sparse_categorical_crossentropy: 0.2217 - val_sparse_categorical_accuracy: 0.9100 - val_scaled_adversarial_loss: 0.1722\n",
      "Epoch 110/1000\n",
      "11/11 [==============================] - 4s 330ms/step - loss: 0.3847 - sparse_categorical_crossentropy: 0.2365 - sparse_categorical_accuracy: 0.9106 - scaled_adversarial_loss: 0.1482 - val_loss: 0.3905 - val_sparse_categorical_crossentropy: 0.2343 - val_sparse_categorical_accuracy: 0.9078 - val_scaled_adversarial_loss: 0.1562\n",
      "Epoch 111/1000\n",
      "11/11 [==============================] - 4s 331ms/step - loss: 0.3870 - sparse_categorical_crossentropy: 0.2398 - sparse_categorical_accuracy: 0.9132 - scaled_adversarial_loss: 0.1472 - val_loss: 0.4016 - val_sparse_categorical_crossentropy: 0.2574 - val_sparse_categorical_accuracy: 0.9033 - val_scaled_adversarial_loss: 0.1442\n",
      "Epoch 112/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.3853 - sparse_categorical_crossentropy: 0.2410 - sparse_categorical_accuracy: 0.9119 - scaled_adversarial_loss: 0.1442 - val_loss: 0.3947 - val_sparse_categorical_crossentropy: 0.2225 - val_sparse_categorical_accuracy: 0.9093 - val_scaled_adversarial_loss: 0.1722\n",
      "Epoch 113/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.3916 - sparse_categorical_crossentropy: 0.2389 - sparse_categorical_accuracy: 0.9126 - scaled_adversarial_loss: 0.1528 - val_loss: 0.3873 - val_sparse_categorical_crossentropy: 0.2375 - val_sparse_categorical_accuracy: 0.9086 - val_scaled_adversarial_loss: 0.1498\n",
      "Epoch 114/1000\n",
      "11/11 [==============================] - 4s 332ms/step - loss: 0.3902 - sparse_categorical_crossentropy: 0.2465 - sparse_categorical_accuracy: 0.9107 - scaled_adversarial_loss: 0.1436 - val_loss: 0.3828 - val_sparse_categorical_crossentropy: 0.2194 - val_sparse_categorical_accuracy: 0.9160 - val_scaled_adversarial_loss: 0.1634\n",
      "Epoch 115/1000\n",
      "11/11 [==============================] - 4s 331ms/step - loss: 0.3841 - sparse_categorical_crossentropy: 0.2360 - sparse_categorical_accuracy: 0.9109 - scaled_adversarial_loss: 0.1481 - val_loss: 0.3820 - val_sparse_categorical_crossentropy: 0.2197 - val_sparse_categorical_accuracy: 0.9152 - val_scaled_adversarial_loss: 0.1623\n",
      "Epoch 116/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.3784 - sparse_categorical_crossentropy: 0.2334 - sparse_categorical_accuracy: 0.9126 - scaled_adversarial_loss: 0.1450 - val_loss: 0.3794 - val_sparse_categorical_crossentropy: 0.2332 - val_sparse_categorical_accuracy: 0.9123 - val_scaled_adversarial_loss: 0.1462\n",
      "Epoch 117/1000\n",
      "11/11 [==============================] - 4s 332ms/step - loss: 0.3759 - sparse_categorical_crossentropy: 0.2316 - sparse_categorical_accuracy: 0.9126 - scaled_adversarial_loss: 0.1443 - val_loss: 0.3792 - val_sparse_categorical_crossentropy: 0.2144 - val_sparse_categorical_accuracy: 0.9093 - val_scaled_adversarial_loss: 0.1648\n",
      "Epoch 118/1000\n",
      "11/11 [==============================] - 4s 332ms/step - loss: 0.3662 - sparse_categorical_crossentropy: 0.2241 - sparse_categorical_accuracy: 0.9141 - scaled_adversarial_loss: 0.1422 - val_loss: 0.3755 - val_sparse_categorical_crossentropy: 0.2072 - val_sparse_categorical_accuracy: 0.9123 - val_scaled_adversarial_loss: 0.1683\n",
      "Epoch 119/1000\n",
      "11/11 [==============================] - 4s 332ms/step - loss: 0.3640 - sparse_categorical_crossentropy: 0.2251 - sparse_categorical_accuracy: 0.9126 - scaled_adversarial_loss: 0.1389 - val_loss: 0.3825 - val_sparse_categorical_crossentropy: 0.2005 - val_sparse_categorical_accuracy: 0.9204 - val_scaled_adversarial_loss: 0.1820\n",
      "Epoch 120/1000\n",
      "11/11 [==============================] - 4s 332ms/step - loss: 0.3735 - sparse_categorical_crossentropy: 0.2309 - sparse_categorical_accuracy: 0.9132 - scaled_adversarial_loss: 0.1425 - val_loss: 0.3709 - val_sparse_categorical_crossentropy: 0.2211 - val_sparse_categorical_accuracy: 0.9100 - val_scaled_adversarial_loss: 0.1498\n",
      "Epoch 121/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.3613 - sparse_categorical_crossentropy: 0.2247 - sparse_categorical_accuracy: 0.9150 - scaled_adversarial_loss: 0.1367 - val_loss: 0.3570 - val_sparse_categorical_crossentropy: 0.2189 - val_sparse_categorical_accuracy: 0.9160 - val_scaled_adversarial_loss: 0.1381\n",
      "Epoch 122/1000\n",
      "11/11 [==============================] - 4s 339ms/step - loss: 0.3489 - sparse_categorical_crossentropy: 0.2203 - sparse_categorical_accuracy: 0.9145 - scaled_adversarial_loss: 0.1286 - val_loss: 0.3518 - val_sparse_categorical_crossentropy: 0.2102 - val_sparse_categorical_accuracy: 0.9152 - val_scaled_adversarial_loss: 0.1416\n",
      "Epoch 123/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.3490 - sparse_categorical_crossentropy: 0.2228 - sparse_categorical_accuracy: 0.9147 - scaled_adversarial_loss: 0.1261 - val_loss: 0.3499 - val_sparse_categorical_crossentropy: 0.2091 - val_sparse_categorical_accuracy: 0.9160 - val_scaled_adversarial_loss: 0.1408\n",
      "Epoch 124/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.3433 - sparse_categorical_crossentropy: 0.2176 - sparse_categorical_accuracy: 0.9174 - scaled_adversarial_loss: 0.1257 - val_loss: 0.3410 - val_sparse_categorical_crossentropy: 0.2071 - val_sparse_categorical_accuracy: 0.9182 - val_scaled_adversarial_loss: 0.1339\n",
      "Epoch 125/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.3384 - sparse_categorical_crossentropy: 0.2132 - sparse_categorical_accuracy: 0.9208 - scaled_adversarial_loss: 0.1252 - val_loss: 0.3416 - val_sparse_categorical_crossentropy: 0.2160 - val_sparse_categorical_accuracy: 0.9197 - val_scaled_adversarial_loss: 0.1257\n",
      "Epoch 126/1000\n",
      "11/11 [==============================] - 4s 331ms/step - loss: 0.3443 - sparse_categorical_crossentropy: 0.2189 - sparse_categorical_accuracy: 0.9206 - scaled_adversarial_loss: 0.1253 - val_loss: 0.3630 - val_sparse_categorical_crossentropy: 0.2119 - val_sparse_categorical_accuracy: 0.9160 - val_scaled_adversarial_loss: 0.1511\n",
      "Epoch 127/1000\n",
      "11/11 [==============================] - 4s 332ms/step - loss: 0.3431 - sparse_categorical_crossentropy: 0.2157 - sparse_categorical_accuracy: 0.9165 - scaled_adversarial_loss: 0.1274 - val_loss: 0.3478 - val_sparse_categorical_crossentropy: 0.2056 - val_sparse_categorical_accuracy: 0.9175 - val_scaled_adversarial_loss: 0.1422\n",
      "Epoch 128/1000\n",
      "11/11 [==============================] - 4s 332ms/step - loss: 0.3388 - sparse_categorical_crossentropy: 0.2164 - sparse_categorical_accuracy: 0.9228 - scaled_adversarial_loss: 0.1224 - val_loss: 0.3362 - val_sparse_categorical_crossentropy: 0.2012 - val_sparse_categorical_accuracy: 0.9234 - val_scaled_adversarial_loss: 0.1350\n",
      "Epoch 129/1000\n",
      "11/11 [==============================] - 4s 331ms/step - loss: 0.3330 - sparse_categorical_crossentropy: 0.2147 - sparse_categorical_accuracy: 0.9221 - scaled_adversarial_loss: 0.1183 - val_loss: 0.3319 - val_sparse_categorical_crossentropy: 0.2051 - val_sparse_categorical_accuracy: 0.9212 - val_scaled_adversarial_loss: 0.1268\n",
      "Epoch 130/1000\n",
      "11/11 [==============================] - 4s 331ms/step - loss: 0.3306 - sparse_categorical_crossentropy: 0.2111 - sparse_categorical_accuracy: 0.9213 - scaled_adversarial_loss: 0.1196 - val_loss: 0.3322 - val_sparse_categorical_crossentropy: 0.2064 - val_sparse_categorical_accuracy: 0.9227 - val_scaled_adversarial_loss: 0.1259\n",
      "Epoch 131/1000\n",
      "11/11 [==============================] - 4s 336ms/step - loss: 0.3299 - sparse_categorical_crossentropy: 0.2110 - sparse_categorical_accuracy: 0.9225 - scaled_adversarial_loss: 0.1189 - val_loss: 0.3296 - val_sparse_categorical_crossentropy: 0.1977 - val_sparse_categorical_accuracy: 0.9234 - val_scaled_adversarial_loss: 0.1319\n",
      "Epoch 132/1000\n",
      "11/11 [==============================] - 4s 336ms/step - loss: 0.3299 - sparse_categorical_crossentropy: 0.2093 - sparse_categorical_accuracy: 0.9245 - scaled_adversarial_loss: 0.1206 - val_loss: 0.3332 - val_sparse_categorical_crossentropy: 0.2031 - val_sparse_categorical_accuracy: 0.9212 - val_scaled_adversarial_loss: 0.1302\n",
      "Epoch 133/1000\n",
      "11/11 [==============================] - 4s 332ms/step - loss: 0.3288 - sparse_categorical_crossentropy: 0.2108 - sparse_categorical_accuracy: 0.9234 - scaled_adversarial_loss: 0.1180 - val_loss: 0.3382 - val_sparse_categorical_crossentropy: 0.1925 - val_sparse_categorical_accuracy: 0.9227 - val_scaled_adversarial_loss: 0.1457\n",
      "Epoch 134/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.3270 - sparse_categorical_crossentropy: 0.2062 - sparse_categorical_accuracy: 0.9210 - scaled_adversarial_loss: 0.1209 - val_loss: 0.3481 - val_sparse_categorical_crossentropy: 0.1985 - val_sparse_categorical_accuracy: 0.9219 - val_scaled_adversarial_loss: 0.1496\n",
      "Epoch 135/1000\n",
      "11/11 [==============================] - 4s 332ms/step - loss: 0.3328 - sparse_categorical_crossentropy: 0.2080 - sparse_categorical_accuracy: 0.9225 - scaled_adversarial_loss: 0.1247 - val_loss: 0.3386 - val_sparse_categorical_crossentropy: 0.2054 - val_sparse_categorical_accuracy: 0.9234 - val_scaled_adversarial_loss: 0.1332\n",
      "Epoch 136/1000\n",
      "11/11 [==============================] - 4s 332ms/step - loss: 0.3284 - sparse_categorical_crossentropy: 0.2115 - sparse_categorical_accuracy: 0.9236 - scaled_adversarial_loss: 0.1169 - val_loss: 0.3276 - val_sparse_categorical_crossentropy: 0.1945 - val_sparse_categorical_accuracy: 0.9234 - val_scaled_adversarial_loss: 0.1331\n",
      "Epoch 137/1000\n",
      "11/11 [==============================] - 4s 331ms/step - loss: 0.3260 - sparse_categorical_crossentropy: 0.2079 - sparse_categorical_accuracy: 0.9241 - scaled_adversarial_loss: 0.1180 - val_loss: 0.3272 - val_sparse_categorical_crossentropy: 0.1979 - val_sparse_categorical_accuracy: 0.9227 - val_scaled_adversarial_loss: 0.1293\n",
      "Epoch 138/1000\n",
      "11/11 [==============================] - 4s 332ms/step - loss: 0.3259 - sparse_categorical_crossentropy: 0.2118 - sparse_categorical_accuracy: 0.9243 - scaled_adversarial_loss: 0.1141 - val_loss: 0.3292 - val_sparse_categorical_crossentropy: 0.1951 - val_sparse_categorical_accuracy: 0.9219 - val_scaled_adversarial_loss: 0.1340\n",
      "Epoch 139/1000\n",
      "11/11 [==============================] - 4s 336ms/step - loss: 0.3169 - sparse_categorical_crossentropy: 0.2000 - sparse_categorical_accuracy: 0.9256 - scaled_adversarial_loss: 0.1169 - val_loss: 0.3223 - val_sparse_categorical_crossentropy: 0.1936 - val_sparse_categorical_accuracy: 0.9242 - val_scaled_adversarial_loss: 0.1287\n",
      "Epoch 140/1000\n",
      "11/11 [==============================] - 4s 332ms/step - loss: 0.3173 - sparse_categorical_crossentropy: 0.2045 - sparse_categorical_accuracy: 0.9260 - scaled_adversarial_loss: 0.1128 - val_loss: 0.3269 - val_sparse_categorical_crossentropy: 0.1965 - val_sparse_categorical_accuracy: 0.9219 - val_scaled_adversarial_loss: 0.1304\n",
      "Epoch 141/1000\n",
      "11/11 [==============================] - 4s 338ms/step - loss: 0.3133 - sparse_categorical_crossentropy: 0.1968 - sparse_categorical_accuracy: 0.9249 - scaled_adversarial_loss: 0.1165 - val_loss: 0.3257 - val_sparse_categorical_crossentropy: 0.1948 - val_sparse_categorical_accuracy: 0.9219 - val_scaled_adversarial_loss: 0.1309\n",
      "Epoch 142/1000\n",
      "11/11 [==============================] - 4s 337ms/step - loss: 0.3185 - sparse_categorical_crossentropy: 0.2003 - sparse_categorical_accuracy: 0.9236 - scaled_adversarial_loss: 0.1182 - val_loss: 0.3165 - val_sparse_categorical_crossentropy: 0.1944 - val_sparse_categorical_accuracy: 0.9219 - val_scaled_adversarial_loss: 0.1221\n",
      "Epoch 143/1000\n",
      "11/11 [==============================] - 4s 331ms/step - loss: 0.3147 - sparse_categorical_crossentropy: 0.2009 - sparse_categorical_accuracy: 0.9256 - scaled_adversarial_loss: 0.1139 - val_loss: 0.3266 - val_sparse_categorical_crossentropy: 0.1879 - val_sparse_categorical_accuracy: 0.9234 - val_scaled_adversarial_loss: 0.1387\n",
      "Epoch 144/1000\n",
      "11/11 [==============================] - 4s 330ms/step - loss: 0.3215 - sparse_categorical_crossentropy: 0.2034 - sparse_categorical_accuracy: 0.9251 - scaled_adversarial_loss: 0.1181 - val_loss: 0.3174 - val_sparse_categorical_crossentropy: 0.1935 - val_sparse_categorical_accuracy: 0.9190 - val_scaled_adversarial_loss: 0.1239\n",
      "Epoch 145/1000\n",
      "11/11 [==============================] - 4s 342ms/step - loss: 0.3111 - sparse_categorical_crossentropy: 0.1985 - sparse_categorical_accuracy: 0.9260 - scaled_adversarial_loss: 0.1125 - val_loss: 0.3275 - val_sparse_categorical_crossentropy: 0.1918 - val_sparse_categorical_accuracy: 0.9227 - val_scaled_adversarial_loss: 0.1357\n",
      "Epoch 146/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.3209 - sparse_categorical_crossentropy: 0.2035 - sparse_categorical_accuracy: 0.9251 - scaled_adversarial_loss: 0.1175 - val_loss: 0.3204 - val_sparse_categorical_crossentropy: 0.1893 - val_sparse_categorical_accuracy: 0.9219 - val_scaled_adversarial_loss: 0.1311\n",
      "Epoch 147/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.3148 - sparse_categorical_crossentropy: 0.2015 - sparse_categorical_accuracy: 0.9279 - scaled_adversarial_loss: 0.1133 - val_loss: 0.3115 - val_sparse_categorical_crossentropy: 0.1872 - val_sparse_categorical_accuracy: 0.9227 - val_scaled_adversarial_loss: 0.1243\n",
      "Epoch 148/1000\n",
      "11/11 [==============================] - 4s 330ms/step - loss: 0.3100 - sparse_categorical_crossentropy: 0.1955 - sparse_categorical_accuracy: 0.9277 - scaled_adversarial_loss: 0.1145 - val_loss: 0.3100 - val_sparse_categorical_crossentropy: 0.1953 - val_sparse_categorical_accuracy: 0.9197 - val_scaled_adversarial_loss: 0.1147\n",
      "Epoch 149/1000\n",
      "11/11 [==============================] - 4s 344ms/step - loss: 0.3100 - sparse_categorical_crossentropy: 0.1974 - sparse_categorical_accuracy: 0.9230 - scaled_adversarial_loss: 0.1127 - val_loss: 0.3300 - val_sparse_categorical_crossentropy: 0.2006 - val_sparse_categorical_accuracy: 0.9182 - val_scaled_adversarial_loss: 0.1294\n",
      "Epoch 150/1000\n",
      "11/11 [==============================] - 4s 335ms/step - loss: 0.3106 - sparse_categorical_crossentropy: 0.1971 - sparse_categorical_accuracy: 0.9253 - scaled_adversarial_loss: 0.1135 - val_loss: 0.3197 - val_sparse_categorical_crossentropy: 0.1947 - val_sparse_categorical_accuracy: 0.9219 - val_scaled_adversarial_loss: 0.1249\n",
      "Epoch 151/1000\n",
      "11/11 [==============================] - 4s 332ms/step - loss: 0.3117 - sparse_categorical_crossentropy: 0.1981 - sparse_categorical_accuracy: 0.9269 - scaled_adversarial_loss: 0.1136 - val_loss: 0.3173 - val_sparse_categorical_crossentropy: 0.1849 - val_sparse_categorical_accuracy: 0.9219 - val_scaled_adversarial_loss: 0.1325\n",
      "Epoch 152/1000\n",
      "11/11 [==============================] - 4s 332ms/step - loss: 0.3146 - sparse_categorical_crossentropy: 0.1995 - sparse_categorical_accuracy: 0.9230 - scaled_adversarial_loss: 0.1151 - val_loss: 0.3171 - val_sparse_categorical_crossentropy: 0.1958 - val_sparse_categorical_accuracy: 0.9234 - val_scaled_adversarial_loss: 0.1212\n",
      "Epoch 153/1000\n",
      "11/11 [==============================] - 4s 336ms/step - loss: 0.3017 - sparse_categorical_crossentropy: 0.1906 - sparse_categorical_accuracy: 0.9275 - scaled_adversarial_loss: 0.1111 - val_loss: 0.3130 - val_sparse_categorical_crossentropy: 0.1826 - val_sparse_categorical_accuracy: 0.9234 - val_scaled_adversarial_loss: 0.1304\n",
      "Epoch 154/1000\n",
      "11/11 [==============================] - 4s 331ms/step - loss: 0.3042 - sparse_categorical_crossentropy: 0.1896 - sparse_categorical_accuracy: 0.9271 - scaled_adversarial_loss: 0.1146 - val_loss: 0.3154 - val_sparse_categorical_crossentropy: 0.1860 - val_sparse_categorical_accuracy: 0.9212 - val_scaled_adversarial_loss: 0.1295\n",
      "Epoch 155/1000\n",
      "11/11 [==============================] - 4s 337ms/step - loss: 0.3035 - sparse_categorical_crossentropy: 0.1923 - sparse_categorical_accuracy: 0.9253 - scaled_adversarial_loss: 0.1112 - val_loss: 0.3078 - val_sparse_categorical_crossentropy: 0.1886 - val_sparse_categorical_accuracy: 0.9212 - val_scaled_adversarial_loss: 0.1192\n",
      "Epoch 156/1000\n",
      "11/11 [==============================] - 4s 340ms/step - loss: 0.3068 - sparse_categorical_crossentropy: 0.1959 - sparse_categorical_accuracy: 0.9251 - scaled_adversarial_loss: 0.1108 - val_loss: 0.3097 - val_sparse_categorical_crossentropy: 0.1887 - val_sparse_categorical_accuracy: 0.9242 - val_scaled_adversarial_loss: 0.1210\n",
      "Epoch 157/1000\n",
      "11/11 [==============================] - 4s 325ms/step - loss: 0.3009 - sparse_categorical_crossentropy: 0.1895 - sparse_categorical_accuracy: 0.9245 - scaled_adversarial_loss: 0.1114 - val_loss: 0.3239 - val_sparse_categorical_crossentropy: 0.1815 - val_sparse_categorical_accuracy: 0.9227 - val_scaled_adversarial_loss: 0.1425\n",
      "Epoch 158/1000\n",
      "11/11 [==============================] - 4s 328ms/step - loss: 0.3050 - sparse_categorical_crossentropy: 0.1907 - sparse_categorical_accuracy: 0.9280 - scaled_adversarial_loss: 0.1143 - val_loss: 0.3119 - val_sparse_categorical_crossentropy: 0.1928 - val_sparse_categorical_accuracy: 0.9212 - val_scaled_adversarial_loss: 0.1191\n",
      "Epoch 159/1000\n",
      "11/11 [==============================] - 4s 327ms/step - loss: 0.3012 - sparse_categorical_crossentropy: 0.1890 - sparse_categorical_accuracy: 0.9292 - scaled_adversarial_loss: 0.1122 - val_loss: 0.3126 - val_sparse_categorical_crossentropy: 0.1891 - val_sparse_categorical_accuracy: 0.9182 - val_scaled_adversarial_loss: 0.1236\n",
      "Epoch 160/1000\n",
      "11/11 [==============================] - 4s 327ms/step - loss: 0.3024 - sparse_categorical_crossentropy: 0.1904 - sparse_categorical_accuracy: 0.9279 - scaled_adversarial_loss: 0.1119 - val_loss: 0.3222 - val_sparse_categorical_crossentropy: 0.1880 - val_sparse_categorical_accuracy: 0.9190 - val_scaled_adversarial_loss: 0.1342\n",
      "Epoch 161/1000\n",
      "11/11 [==============================] - 4s 326ms/step - loss: 0.2975 - sparse_categorical_crossentropy: 0.1878 - sparse_categorical_accuracy: 0.9277 - scaled_adversarial_loss: 0.1097 - val_loss: 0.3117 - val_sparse_categorical_crossentropy: 0.1793 - val_sparse_categorical_accuracy: 0.9219 - val_scaled_adversarial_loss: 0.1324\n",
      "Epoch 162/1000\n",
      "11/11 [==============================] - 4s 325ms/step - loss: 0.3036 - sparse_categorical_crossentropy: 0.1910 - sparse_categorical_accuracy: 0.9273 - scaled_adversarial_loss: 0.1126 - val_loss: 0.3036 - val_sparse_categorical_crossentropy: 0.1778 - val_sparse_categorical_accuracy: 0.9227 - val_scaled_adversarial_loss: 0.1258\n",
      "Epoch 163/1000\n",
      "11/11 [==============================] - 4s 328ms/step - loss: 0.2979 - sparse_categorical_crossentropy: 0.1885 - sparse_categorical_accuracy: 0.9286 - scaled_adversarial_loss: 0.1094 - val_loss: 0.3065 - val_sparse_categorical_crossentropy: 0.1760 - val_sparse_categorical_accuracy: 0.9279 - val_scaled_adversarial_loss: 0.1305\n",
      "Epoch 164/1000\n",
      "11/11 [==============================] - 4s 324ms/step - loss: 0.2939 - sparse_categorical_crossentropy: 0.1831 - sparse_categorical_accuracy: 0.9288 - scaled_adversarial_loss: 0.1108 - val_loss: 0.2976 - val_sparse_categorical_crossentropy: 0.1826 - val_sparse_categorical_accuracy: 0.9234 - val_scaled_adversarial_loss: 0.1150\n",
      "Epoch 165/1000\n",
      "11/11 [==============================] - 4s 323ms/step - loss: 0.2907 - sparse_categorical_crossentropy: 0.1831 - sparse_categorical_accuracy: 0.9305 - scaled_adversarial_loss: 0.1077 - val_loss: 0.3035 - val_sparse_categorical_crossentropy: 0.1905 - val_sparse_categorical_accuracy: 0.9286 - val_scaled_adversarial_loss: 0.1130\n",
      "Epoch 166/1000\n",
      "11/11 [==============================] - 4s 323ms/step - loss: 0.3002 - sparse_categorical_crossentropy: 0.1889 - sparse_categorical_accuracy: 0.9293 - scaled_adversarial_loss: 0.1113 - val_loss: 0.3008 - val_sparse_categorical_crossentropy: 0.1827 - val_sparse_categorical_accuracy: 0.9219 - val_scaled_adversarial_loss: 0.1181\n",
      "Epoch 167/1000\n",
      "11/11 [==============================] - 4s 327ms/step - loss: 0.2849 - sparse_categorical_crossentropy: 0.1802 - sparse_categorical_accuracy: 0.9269 - scaled_adversarial_loss: 0.1047 - val_loss: 0.3051 - val_sparse_categorical_crossentropy: 0.1710 - val_sparse_categorical_accuracy: 0.9271 - val_scaled_adversarial_loss: 0.1341\n",
      "Epoch 168/1000\n",
      "11/11 [==============================] - 4s 326ms/step - loss: 0.2843 - sparse_categorical_crossentropy: 0.1771 - sparse_categorical_accuracy: 0.9277 - scaled_adversarial_loss: 0.1072 - val_loss: 0.2894 - val_sparse_categorical_crossentropy: 0.1730 - val_sparse_categorical_accuracy: 0.9212 - val_scaled_adversarial_loss: 0.1164\n",
      "Epoch 169/1000\n",
      "11/11 [==============================] - 4s 325ms/step - loss: 0.2860 - sparse_categorical_crossentropy: 0.1798 - sparse_categorical_accuracy: 0.9342 - scaled_adversarial_loss: 0.1062 - val_loss: 0.2875 - val_sparse_categorical_crossentropy: 0.1742 - val_sparse_categorical_accuracy: 0.9249 - val_scaled_adversarial_loss: 0.1132\n",
      "Epoch 170/1000\n",
      "11/11 [==============================] - 4s 327ms/step - loss: 0.2785 - sparse_categorical_crossentropy: 0.1713 - sparse_categorical_accuracy: 0.9329 - scaled_adversarial_loss: 0.1072 - val_loss: 0.2845 - val_sparse_categorical_crossentropy: 0.1699 - val_sparse_categorical_accuracy: 0.9227 - val_scaled_adversarial_loss: 0.1146\n",
      "Epoch 171/1000\n",
      "11/11 [==============================] - 4s 326ms/step - loss: 0.2771 - sparse_categorical_crossentropy: 0.1736 - sparse_categorical_accuracy: 0.9305 - scaled_adversarial_loss: 0.1035 - val_loss: 0.2884 - val_sparse_categorical_crossentropy: 0.1690 - val_sparse_categorical_accuracy: 0.9242 - val_scaled_adversarial_loss: 0.1194\n",
      "Epoch 172/1000\n",
      "11/11 [==============================] - 4s 326ms/step - loss: 0.2833 - sparse_categorical_crossentropy: 0.1772 - sparse_categorical_accuracy: 0.9279 - scaled_adversarial_loss: 0.1061 - val_loss: 0.2922 - val_sparse_categorical_crossentropy: 0.1698 - val_sparse_categorical_accuracy: 0.9271 - val_scaled_adversarial_loss: 0.1224\n",
      "Epoch 173/1000\n",
      "11/11 [==============================] - 4s 325ms/step - loss: 0.2810 - sparse_categorical_crossentropy: 0.1769 - sparse_categorical_accuracy: 0.9325 - scaled_adversarial_loss: 0.1041 - val_loss: 0.2839 - val_sparse_categorical_crossentropy: 0.1689 - val_sparse_categorical_accuracy: 0.9227 - val_scaled_adversarial_loss: 0.1149\n",
      "Epoch 174/1000\n",
      "11/11 [==============================] - 4s 326ms/step - loss: 0.2878 - sparse_categorical_crossentropy: 0.1777 - sparse_categorical_accuracy: 0.9299 - scaled_adversarial_loss: 0.1102 - val_loss: 0.2878 - val_sparse_categorical_crossentropy: 0.1756 - val_sparse_categorical_accuracy: 0.9234 - val_scaled_adversarial_loss: 0.1122\n",
      "Epoch 175/1000\n",
      "11/11 [==============================] - 4s 326ms/step - loss: 0.2874 - sparse_categorical_crossentropy: 0.1802 - sparse_categorical_accuracy: 0.9303 - scaled_adversarial_loss: 0.1073 - val_loss: 0.2844 - val_sparse_categorical_crossentropy: 0.1757 - val_sparse_categorical_accuracy: 0.9257 - val_scaled_adversarial_loss: 0.1087\n",
      "Epoch 176/1000\n",
      "11/11 [==============================] - 4s 327ms/step - loss: 0.2766 - sparse_categorical_crossentropy: 0.1751 - sparse_categorical_accuracy: 0.9310 - scaled_adversarial_loss: 0.1015 - val_loss: 0.2825 - val_sparse_categorical_crossentropy: 0.1682 - val_sparse_categorical_accuracy: 0.9227 - val_scaled_adversarial_loss: 0.1142\n",
      "Epoch 177/1000\n",
      "11/11 [==============================] - 4s 324ms/step - loss: 0.2721 - sparse_categorical_crossentropy: 0.1695 - sparse_categorical_accuracy: 0.9310 - scaled_adversarial_loss: 0.1026 - val_loss: 0.2800 - val_sparse_categorical_crossentropy: 0.1645 - val_sparse_categorical_accuracy: 0.9249 - val_scaled_adversarial_loss: 0.1155\n",
      "Epoch 178/1000\n",
      "11/11 [==============================] - 4s 326ms/step - loss: 0.2740 - sparse_categorical_crossentropy: 0.1715 - sparse_categorical_accuracy: 0.9338 - scaled_adversarial_loss: 0.1025 - val_loss: 0.2781 - val_sparse_categorical_crossentropy: 0.1644 - val_sparse_categorical_accuracy: 0.9264 - val_scaled_adversarial_loss: 0.1137\n",
      "Epoch 179/1000\n",
      "11/11 [==============================] - 4s 326ms/step - loss: 0.2719 - sparse_categorical_crossentropy: 0.1694 - sparse_categorical_accuracy: 0.9316 - scaled_adversarial_loss: 0.1025 - val_loss: 0.2751 - val_sparse_categorical_crossentropy: 0.1660 - val_sparse_categorical_accuracy: 0.9264 - val_scaled_adversarial_loss: 0.1090\n",
      "Epoch 180/1000\n",
      "11/11 [==============================] - 4s 327ms/step - loss: 0.2709 - sparse_categorical_crossentropy: 0.1699 - sparse_categorical_accuracy: 0.9344 - scaled_adversarial_loss: 0.1009 - val_loss: 0.2764 - val_sparse_categorical_crossentropy: 0.1633 - val_sparse_categorical_accuracy: 0.9301 - val_scaled_adversarial_loss: 0.1131\n",
      "Epoch 181/1000\n",
      "11/11 [==============================] - 4s 328ms/step - loss: 0.2720 - sparse_categorical_crossentropy: 0.1704 - sparse_categorical_accuracy: 0.9345 - scaled_adversarial_loss: 0.1017 - val_loss: 0.2944 - val_sparse_categorical_crossentropy: 0.1687 - val_sparse_categorical_accuracy: 0.9294 - val_scaled_adversarial_loss: 0.1258\n",
      "Epoch 182/1000\n",
      "11/11 [==============================] - 4s 323ms/step - loss: 0.2730 - sparse_categorical_crossentropy: 0.1716 - sparse_categorical_accuracy: 0.9325 - scaled_adversarial_loss: 0.1015 - val_loss: 0.2825 - val_sparse_categorical_crossentropy: 0.1637 - val_sparse_categorical_accuracy: 0.9279 - val_scaled_adversarial_loss: 0.1188\n",
      "Epoch 183/1000\n",
      "11/11 [==============================] - 4s 329ms/step - loss: 0.2676 - sparse_categorical_crossentropy: 0.1667 - sparse_categorical_accuracy: 0.9349 - scaled_adversarial_loss: 0.1009 - val_loss: 0.2793 - val_sparse_categorical_crossentropy: 0.1630 - val_sparse_categorical_accuracy: 0.9294 - val_scaled_adversarial_loss: 0.1163\n",
      "Epoch 184/1000\n",
      "11/11 [==============================] - 4s 326ms/step - loss: 0.2640 - sparse_categorical_crossentropy: 0.1642 - sparse_categorical_accuracy: 0.9334 - scaled_adversarial_loss: 0.0998 - val_loss: 0.2870 - val_sparse_categorical_crossentropy: 0.1618 - val_sparse_categorical_accuracy: 0.9294 - val_scaled_adversarial_loss: 0.1253\n",
      "Epoch 185/1000\n",
      "11/11 [==============================] - 4s 330ms/step - loss: 0.2736 - sparse_categorical_crossentropy: 0.1728 - sparse_categorical_accuracy: 0.9295 - scaled_adversarial_loss: 0.1009 - val_loss: 0.2809 - val_sparse_categorical_crossentropy: 0.1632 - val_sparse_categorical_accuracy: 0.9294 - val_scaled_adversarial_loss: 0.1176\n",
      "Epoch 186/1000\n",
      "11/11 [==============================] - 4s 332ms/step - loss: 0.2694 - sparse_categorical_crossentropy: 0.1663 - sparse_categorical_accuracy: 0.9358 - scaled_adversarial_loss: 0.1031 - val_loss: 0.2742 - val_sparse_categorical_crossentropy: 0.1665 - val_sparse_categorical_accuracy: 0.9242 - val_scaled_adversarial_loss: 0.1077\n",
      "Epoch 187/1000\n",
      "11/11 [==============================] - 4s 324ms/step - loss: 0.2717 - sparse_categorical_crossentropy: 0.1719 - sparse_categorical_accuracy: 0.9332 - scaled_adversarial_loss: 0.0998 - val_loss: 0.2742 - val_sparse_categorical_crossentropy: 0.1639 - val_sparse_categorical_accuracy: 0.9286 - val_scaled_adversarial_loss: 0.1103\n",
      "Epoch 188/1000\n",
      "11/11 [==============================] - 4s 330ms/step - loss: 0.2634 - sparse_categorical_crossentropy: 0.1622 - sparse_categorical_accuracy: 0.9375 - scaled_adversarial_loss: 0.1013 - val_loss: 0.2917 - val_sparse_categorical_crossentropy: 0.1650 - val_sparse_categorical_accuracy: 0.9309 - val_scaled_adversarial_loss: 0.1267\n",
      "Epoch 189/1000\n",
      "11/11 [==============================] - 4s 325ms/step - loss: 0.2695 - sparse_categorical_crossentropy: 0.1674 - sparse_categorical_accuracy: 0.9357 - scaled_adversarial_loss: 0.1022 - val_loss: 0.2776 - val_sparse_categorical_crossentropy: 0.1644 - val_sparse_categorical_accuracy: 0.9279 - val_scaled_adversarial_loss: 0.1132\n",
      "Epoch 190/1000\n",
      "11/11 [==============================] - 4s 331ms/step - loss: 0.2622 - sparse_categorical_crossentropy: 0.1644 - sparse_categorical_accuracy: 0.9312 - scaled_adversarial_loss: 0.0978 - val_loss: 0.2728 - val_sparse_categorical_crossentropy: 0.1612 - val_sparse_categorical_accuracy: 0.9264 - val_scaled_adversarial_loss: 0.1116\n",
      "Epoch 191/1000\n",
      "11/11 [==============================] - 4s 326ms/step - loss: 0.2633 - sparse_categorical_crossentropy: 0.1648 - sparse_categorical_accuracy: 0.9334 - scaled_adversarial_loss: 0.0986 - val_loss: 0.2747 - val_sparse_categorical_crossentropy: 0.1612 - val_sparse_categorical_accuracy: 0.9294 - val_scaled_adversarial_loss: 0.1135\n",
      "Epoch 192/1000\n",
      "11/11 [==============================] - 4s 325ms/step - loss: 0.2601 - sparse_categorical_crossentropy: 0.1605 - sparse_categorical_accuracy: 0.9368 - scaled_adversarial_loss: 0.0996 - val_loss: 0.2717 - val_sparse_categorical_crossentropy: 0.1623 - val_sparse_categorical_accuracy: 0.9286 - val_scaled_adversarial_loss: 0.1095\n",
      "Epoch 193/1000\n",
      "11/11 [==============================] - 4s 328ms/step - loss: 0.2636 - sparse_categorical_crossentropy: 0.1646 - sparse_categorical_accuracy: 0.9344 - scaled_adversarial_loss: 0.0990 - val_loss: 0.2808 - val_sparse_categorical_crossentropy: 0.1639 - val_sparse_categorical_accuracy: 0.9257 - val_scaled_adversarial_loss: 0.1169\n",
      "Epoch 194/1000\n",
      "11/11 [==============================] - 4s 325ms/step - loss: 0.2626 - sparse_categorical_crossentropy: 0.1630 - sparse_categorical_accuracy: 0.9358 - scaled_adversarial_loss: 0.0996 - val_loss: 0.2757 - val_sparse_categorical_crossentropy: 0.1613 - val_sparse_categorical_accuracy: 0.9279 - val_scaled_adversarial_loss: 0.1143\n",
      "Epoch 195/1000\n",
      "11/11 [==============================] - 4s 324ms/step - loss: 0.2667 - sparse_categorical_crossentropy: 0.1650 - sparse_categorical_accuracy: 0.9360 - scaled_adversarial_loss: 0.1017 - val_loss: 0.2724 - val_sparse_categorical_crossentropy: 0.1594 - val_sparse_categorical_accuracy: 0.9323 - val_scaled_adversarial_loss: 0.1130\n",
      "Epoch 196/1000\n",
      "11/11 [==============================] - 4s 335ms/step - loss: 0.2611 - sparse_categorical_crossentropy: 0.1613 - sparse_categorical_accuracy: 0.9375 - scaled_adversarial_loss: 0.0998 - val_loss: 0.2721 - val_sparse_categorical_crossentropy: 0.1612 - val_sparse_categorical_accuracy: 0.9323 - val_scaled_adversarial_loss: 0.1108\n",
      "Epoch 197/1000\n",
      "11/11 [==============================] - 4s 325ms/step - loss: 0.2605 - sparse_categorical_crossentropy: 0.1594 - sparse_categorical_accuracy: 0.9401 - scaled_adversarial_loss: 0.1012 - val_loss: 0.2833 - val_sparse_categorical_crossentropy: 0.1700 - val_sparse_categorical_accuracy: 0.9234 - val_scaled_adversarial_loss: 0.1132\n",
      "Epoch 198/1000\n",
      "11/11 [==============================] - 4s 329ms/step - loss: 0.2622 - sparse_categorical_crossentropy: 0.1614 - sparse_categorical_accuracy: 0.9347 - scaled_adversarial_loss: 0.1008 - val_loss: 0.2928 - val_sparse_categorical_crossentropy: 0.1612 - val_sparse_categorical_accuracy: 0.9279 - val_scaled_adversarial_loss: 0.1316\n",
      "Epoch 199/1000\n",
      "11/11 [==============================] - 4s 327ms/step - loss: 0.2614 - sparse_categorical_crossentropy: 0.1623 - sparse_categorical_accuracy: 0.9358 - scaled_adversarial_loss: 0.0991 - val_loss: 0.2698 - val_sparse_categorical_crossentropy: 0.1568 - val_sparse_categorical_accuracy: 0.9294 - val_scaled_adversarial_loss: 0.1130\n",
      "Epoch 200/1000\n",
      "11/11 [==============================] - 4s 323ms/step - loss: 0.2632 - sparse_categorical_crossentropy: 0.1609 - sparse_categorical_accuracy: 0.9370 - scaled_adversarial_loss: 0.1023 - val_loss: 0.2629 - val_sparse_categorical_crossentropy: 0.1611 - val_sparse_categorical_accuracy: 0.9309 - val_scaled_adversarial_loss: 0.1019\n",
      "Epoch 201/1000\n",
      "11/11 [==============================] - 4s 322ms/step - loss: 0.2596 - sparse_categorical_crossentropy: 0.1632 - sparse_categorical_accuracy: 0.9362 - scaled_adversarial_loss: 0.0964 - val_loss: 0.2659 - val_sparse_categorical_crossentropy: 0.1574 - val_sparse_categorical_accuracy: 0.9316 - val_scaled_adversarial_loss: 0.1085\n",
      "Epoch 202/1000\n",
      "11/11 [==============================] - 4s 324ms/step - loss: 0.2515 - sparse_categorical_crossentropy: 0.1546 - sparse_categorical_accuracy: 0.9401 - scaled_adversarial_loss: 0.0970 - val_loss: 0.2722 - val_sparse_categorical_crossentropy: 0.1614 - val_sparse_categorical_accuracy: 0.9301 - val_scaled_adversarial_loss: 0.1108\n",
      "Epoch 203/1000\n",
      "11/11 [==============================] - 4s 324ms/step - loss: 0.2588 - sparse_categorical_crossentropy: 0.1591 - sparse_categorical_accuracy: 0.9358 - scaled_adversarial_loss: 0.0997 - val_loss: 0.2642 - val_sparse_categorical_crossentropy: 0.1583 - val_sparse_categorical_accuracy: 0.9331 - val_scaled_adversarial_loss: 0.1060\n",
      "Epoch 204/1000\n",
      "11/11 [==============================] - 4s 324ms/step - loss: 0.2492 - sparse_categorical_crossentropy: 0.1556 - sparse_categorical_accuracy: 0.9403 - scaled_adversarial_loss: 0.0936 - val_loss: 0.2607 - val_sparse_categorical_crossentropy: 0.1559 - val_sparse_categorical_accuracy: 0.9286 - val_scaled_adversarial_loss: 0.1048\n",
      "Epoch 205/1000\n",
      "11/11 [==============================] - 4s 328ms/step - loss: 0.2500 - sparse_categorical_crossentropy: 0.1541 - sparse_categorical_accuracy: 0.9373 - scaled_adversarial_loss: 0.0960 - val_loss: 0.2720 - val_sparse_categorical_crossentropy: 0.1619 - val_sparse_categorical_accuracy: 0.9294 - val_scaled_adversarial_loss: 0.1100\n",
      "Epoch 206/1000\n",
      "11/11 [==============================] - 4s 329ms/step - loss: 0.2528 - sparse_categorical_crossentropy: 0.1556 - sparse_categorical_accuracy: 0.9388 - scaled_adversarial_loss: 0.0972 - val_loss: 0.2662 - val_sparse_categorical_crossentropy: 0.1567 - val_sparse_categorical_accuracy: 0.9286 - val_scaled_adversarial_loss: 0.1095\n",
      "Epoch 207/1000\n",
      "11/11 [==============================] - 4s 326ms/step - loss: 0.2482 - sparse_categorical_crossentropy: 0.1535 - sparse_categorical_accuracy: 0.9386 - scaled_adversarial_loss: 0.0947 - val_loss: 0.2737 - val_sparse_categorical_crossentropy: 0.1568 - val_sparse_categorical_accuracy: 0.9316 - val_scaled_adversarial_loss: 0.1169\n",
      "Epoch 208/1000\n",
      "11/11 [==============================] - 4s 328ms/step - loss: 0.2527 - sparse_categorical_crossentropy: 0.1569 - sparse_categorical_accuracy: 0.9401 - scaled_adversarial_loss: 0.0958 - val_loss: 0.2827 - val_sparse_categorical_crossentropy: 0.1570 - val_sparse_categorical_accuracy: 0.9316 - val_scaled_adversarial_loss: 0.1257\n",
      "Epoch 209/1000\n",
      "11/11 [==============================] - 4s 326ms/step - loss: 0.2527 - sparse_categorical_crossentropy: 0.1558 - sparse_categorical_accuracy: 0.9379 - scaled_adversarial_loss: 0.0969 - val_loss: 0.2712 - val_sparse_categorical_crossentropy: 0.1540 - val_sparse_categorical_accuracy: 0.9309 - val_scaled_adversarial_loss: 0.1173\n",
      "Epoch 210/1000\n",
      "11/11 [==============================] - 4s 325ms/step - loss: 0.2516 - sparse_categorical_crossentropy: 0.1523 - sparse_categorical_accuracy: 0.9416 - scaled_adversarial_loss: 0.0993 - val_loss: 0.2668 - val_sparse_categorical_crossentropy: 0.1589 - val_sparse_categorical_accuracy: 0.9346 - val_scaled_adversarial_loss: 0.1078\n",
      "Epoch 211/1000\n",
      "11/11 [==============================] - 4s 327ms/step - loss: 0.2485 - sparse_categorical_crossentropy: 0.1509 - sparse_categorical_accuracy: 0.9392 - scaled_adversarial_loss: 0.0976 - val_loss: 0.2637 - val_sparse_categorical_crossentropy: 0.1537 - val_sparse_categorical_accuracy: 0.9338 - val_scaled_adversarial_loss: 0.1100\n",
      "Epoch 212/1000\n",
      "11/11 [==============================] - 4s 326ms/step - loss: 0.2490 - sparse_categorical_crossentropy: 0.1560 - sparse_categorical_accuracy: 0.9372 - scaled_adversarial_loss: 0.0931 - val_loss: 0.2575 - val_sparse_categorical_crossentropy: 0.1536 - val_sparse_categorical_accuracy: 0.9353 - val_scaled_adversarial_loss: 0.1039\n",
      "Epoch 213/1000\n",
      "11/11 [==============================] - 4s 325ms/step - loss: 0.2495 - sparse_categorical_crossentropy: 0.1520 - sparse_categorical_accuracy: 0.9422 - scaled_adversarial_loss: 0.0975 - val_loss: 0.2640 - val_sparse_categorical_crossentropy: 0.1505 - val_sparse_categorical_accuracy: 0.9338 - val_scaled_adversarial_loss: 0.1135\n",
      "Epoch 214/1000\n",
      "11/11 [==============================] - 4s 326ms/step - loss: 0.2464 - sparse_categorical_crossentropy: 0.1509 - sparse_categorical_accuracy: 0.9392 - scaled_adversarial_loss: 0.0955 - val_loss: 0.2612 - val_sparse_categorical_crossentropy: 0.1576 - val_sparse_categorical_accuracy: 0.9294 - val_scaled_adversarial_loss: 0.1036\n",
      "Epoch 215/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.2483 - sparse_categorical_crossentropy: 0.1525 - sparse_categorical_accuracy: 0.9398 - scaled_adversarial_loss: 0.0958 - val_loss: 0.2617 - val_sparse_categorical_crossentropy: 0.1556 - val_sparse_categorical_accuracy: 0.9338 - val_scaled_adversarial_loss: 0.1061\n",
      "Epoch 216/1000\n",
      "11/11 [==============================] - 4s 329ms/step - loss: 0.2493 - sparse_categorical_crossentropy: 0.1555 - sparse_categorical_accuracy: 0.9425 - scaled_adversarial_loss: 0.0938 - val_loss: 0.2555 - val_sparse_categorical_crossentropy: 0.1485 - val_sparse_categorical_accuracy: 0.9368 - val_scaled_adversarial_loss: 0.1070\n",
      "Epoch 217/1000\n",
      "11/11 [==============================] - 4s 331ms/step - loss: 0.2405 - sparse_categorical_crossentropy: 0.1446 - sparse_categorical_accuracy: 0.9464 - scaled_adversarial_loss: 0.0959 - val_loss: 0.2650 - val_sparse_categorical_crossentropy: 0.1543 - val_sparse_categorical_accuracy: 0.9323 - val_scaled_adversarial_loss: 0.1107\n",
      "Epoch 218/1000\n",
      "11/11 [==============================] - 4s 327ms/step - loss: 0.2416 - sparse_categorical_crossentropy: 0.1466 - sparse_categorical_accuracy: 0.9414 - scaled_adversarial_loss: 0.0951 - val_loss: 0.2602 - val_sparse_categorical_crossentropy: 0.1491 - val_sparse_categorical_accuracy: 0.9368 - val_scaled_adversarial_loss: 0.1111\n",
      "Epoch 219/1000\n",
      "11/11 [==============================] - 4s 327ms/step - loss: 0.2361 - sparse_categorical_crossentropy: 0.1447 - sparse_categorical_accuracy: 0.9438 - scaled_adversarial_loss: 0.0913 - val_loss: 0.2616 - val_sparse_categorical_crossentropy: 0.1449 - val_sparse_categorical_accuracy: 0.9390 - val_scaled_adversarial_loss: 0.1167\n",
      "Epoch 220/1000\n",
      "11/11 [==============================] - 4s 329ms/step - loss: 0.2461 - sparse_categorical_crossentropy: 0.1530 - sparse_categorical_accuracy: 0.9403 - scaled_adversarial_loss: 0.0932 - val_loss: 0.2610 - val_sparse_categorical_crossentropy: 0.1496 - val_sparse_categorical_accuracy: 0.9331 - val_scaled_adversarial_loss: 0.1114\n",
      "Epoch 221/1000\n",
      "11/11 [==============================] - 4s 331ms/step - loss: 0.2481 - sparse_categorical_crossentropy: 0.1535 - sparse_categorical_accuracy: 0.9379 - scaled_adversarial_loss: 0.0946 - val_loss: 0.2594 - val_sparse_categorical_crossentropy: 0.1500 - val_sparse_categorical_accuracy: 0.9368 - val_scaled_adversarial_loss: 0.1094\n",
      "Epoch 222/1000\n",
      "11/11 [==============================] - 4s 328ms/step - loss: 0.2393 - sparse_categorical_crossentropy: 0.1465 - sparse_categorical_accuracy: 0.9437 - scaled_adversarial_loss: 0.0928 - val_loss: 0.2550 - val_sparse_categorical_crossentropy: 0.1468 - val_sparse_categorical_accuracy: 0.9375 - val_scaled_adversarial_loss: 0.1082\n",
      "Epoch 223/1000\n",
      "11/11 [==============================] - 4s 331ms/step - loss: 0.2342 - sparse_categorical_crossentropy: 0.1440 - sparse_categorical_accuracy: 0.9453 - scaled_adversarial_loss: 0.0902 - val_loss: 0.2530 - val_sparse_categorical_crossentropy: 0.1488 - val_sparse_categorical_accuracy: 0.9383 - val_scaled_adversarial_loss: 0.1042\n",
      "Epoch 224/1000\n",
      "11/11 [==============================] - 4s 323ms/step - loss: 0.2407 - sparse_categorical_crossentropy: 0.1492 - sparse_categorical_accuracy: 0.9394 - scaled_adversarial_loss: 0.0916 - val_loss: 0.2525 - val_sparse_categorical_crossentropy: 0.1464 - val_sparse_categorical_accuracy: 0.9361 - val_scaled_adversarial_loss: 0.1061\n",
      "Epoch 225/1000\n",
      "11/11 [==============================] - 4s 324ms/step - loss: 0.2468 - sparse_categorical_crossentropy: 0.1496 - sparse_categorical_accuracy: 0.9416 - scaled_adversarial_loss: 0.0972 - val_loss: 0.2849 - val_sparse_categorical_crossentropy: 0.1500 - val_sparse_categorical_accuracy: 0.9368 - val_scaled_adversarial_loss: 0.1350\n",
      "Epoch 226/1000\n",
      "11/11 [==============================] - 4s 324ms/step - loss: 0.2517 - sparse_categorical_crossentropy: 0.1541 - sparse_categorical_accuracy: 0.9409 - scaled_adversarial_loss: 0.0975 - val_loss: 0.2568 - val_sparse_categorical_crossentropy: 0.1510 - val_sparse_categorical_accuracy: 0.9368 - val_scaled_adversarial_loss: 0.1058\n",
      "Epoch 227/1000\n",
      "11/11 [==============================] - 4s 328ms/step - loss: 0.2418 - sparse_categorical_crossentropy: 0.1483 - sparse_categorical_accuracy: 0.9422 - scaled_adversarial_loss: 0.0935 - val_loss: 0.2552 - val_sparse_categorical_crossentropy: 0.1487 - val_sparse_categorical_accuracy: 0.9368 - val_scaled_adversarial_loss: 0.1065\n",
      "Epoch 228/1000\n",
      "11/11 [==============================] - 4s 328ms/step - loss: 0.2364 - sparse_categorical_crossentropy: 0.1444 - sparse_categorical_accuracy: 0.9424 - scaled_adversarial_loss: 0.0920 - val_loss: 0.2514 - val_sparse_categorical_crossentropy: 0.1485 - val_sparse_categorical_accuracy: 0.9383 - val_scaled_adversarial_loss: 0.1029\n",
      "Epoch 229/1000\n",
      "11/11 [==============================] - 4s 327ms/step - loss: 0.2371 - sparse_categorical_crossentropy: 0.1450 - sparse_categorical_accuracy: 0.9416 - scaled_adversarial_loss: 0.0922 - val_loss: 0.2507 - val_sparse_categorical_crossentropy: 0.1509 - val_sparse_categorical_accuracy: 0.9428 - val_scaled_adversarial_loss: 0.0998\n",
      "Epoch 230/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.2394 - sparse_categorical_crossentropy: 0.1480 - sparse_categorical_accuracy: 0.9470 - scaled_adversarial_loss: 0.0914 - val_loss: 0.2531 - val_sparse_categorical_crossentropy: 0.1420 - val_sparse_categorical_accuracy: 0.9413 - val_scaled_adversarial_loss: 0.1111\n",
      "Epoch 231/1000\n",
      "11/11 [==============================] - 4s 335ms/step - loss: 0.2345 - sparse_categorical_crossentropy: 0.1416 - sparse_categorical_accuracy: 0.9483 - scaled_adversarial_loss: 0.0929 - val_loss: 0.2928 - val_sparse_categorical_crossentropy: 0.1615 - val_sparse_categorical_accuracy: 0.9346 - val_scaled_adversarial_loss: 0.1313\n",
      "Epoch 232/1000\n",
      "11/11 [==============================] - 4s 336ms/step - loss: 0.2479 - sparse_categorical_crossentropy: 0.1501 - sparse_categorical_accuracy: 0.9446 - scaled_adversarial_loss: 0.0978 - val_loss: 0.2908 - val_sparse_categorical_crossentropy: 0.1628 - val_sparse_categorical_accuracy: 0.9294 - val_scaled_adversarial_loss: 0.1280\n",
      "Epoch 233/1000\n",
      "11/11 [==============================] - 4s 330ms/step - loss: 0.2502 - sparse_categorical_crossentropy: 0.1503 - sparse_categorical_accuracy: 0.9420 - scaled_adversarial_loss: 0.0999 - val_loss: 0.2538 - val_sparse_categorical_crossentropy: 0.1444 - val_sparse_categorical_accuracy: 0.9361 - val_scaled_adversarial_loss: 0.1095\n",
      "Epoch 234/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.2310 - sparse_categorical_crossentropy: 0.1407 - sparse_categorical_accuracy: 0.9463 - scaled_adversarial_loss: 0.0904 - val_loss: 0.2526 - val_sparse_categorical_crossentropy: 0.1460 - val_sparse_categorical_accuracy: 0.9413 - val_scaled_adversarial_loss: 0.1066\n",
      "Epoch 235/1000\n",
      "11/11 [==============================] - 4s 331ms/step - loss: 0.2358 - sparse_categorical_crossentropy: 0.1453 - sparse_categorical_accuracy: 0.9463 - scaled_adversarial_loss: 0.0905 - val_loss: 0.2483 - val_sparse_categorical_crossentropy: 0.1497 - val_sparse_categorical_accuracy: 0.9323 - val_scaled_adversarial_loss: 0.0986\n",
      "Epoch 236/1000\n",
      "11/11 [==============================] - 4s 332ms/step - loss: 0.2381 - sparse_categorical_crossentropy: 0.1450 - sparse_categorical_accuracy: 0.9453 - scaled_adversarial_loss: 0.0931 - val_loss: 0.2499 - val_sparse_categorical_crossentropy: 0.1464 - val_sparse_categorical_accuracy: 0.9368 - val_scaled_adversarial_loss: 0.1034\n",
      "Epoch 237/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.2319 - sparse_categorical_crossentropy: 0.1366 - sparse_categorical_accuracy: 0.9468 - scaled_adversarial_loss: 0.0953 - val_loss: 0.2471 - val_sparse_categorical_crossentropy: 0.1437 - val_sparse_categorical_accuracy: 0.9413 - val_scaled_adversarial_loss: 0.1033\n",
      "Epoch 238/1000\n",
      "11/11 [==============================] - 4s 332ms/step - loss: 0.2372 - sparse_categorical_crossentropy: 0.1423 - sparse_categorical_accuracy: 0.9440 - scaled_adversarial_loss: 0.0949 - val_loss: 0.2447 - val_sparse_categorical_crossentropy: 0.1443 - val_sparse_categorical_accuracy: 0.9413 - val_scaled_adversarial_loss: 0.1003\n",
      "Epoch 239/1000\n",
      "11/11 [==============================] - 4s 331ms/step - loss: 0.2420 - sparse_categorical_crossentropy: 0.1492 - sparse_categorical_accuracy: 0.9427 - scaled_adversarial_loss: 0.0928 - val_loss: 0.2605 - val_sparse_categorical_crossentropy: 0.1544 - val_sparse_categorical_accuracy: 0.9390 - val_scaled_adversarial_loss: 0.1061\n",
      "Epoch 240/1000\n",
      "11/11 [==============================] - 4s 332ms/step - loss: 0.2381 - sparse_categorical_crossentropy: 0.1456 - sparse_categorical_accuracy: 0.9429 - scaled_adversarial_loss: 0.0925 - val_loss: 0.2464 - val_sparse_categorical_crossentropy: 0.1420 - val_sparse_categorical_accuracy: 0.9398 - val_scaled_adversarial_loss: 0.1044\n",
      "Epoch 241/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.2296 - sparse_categorical_crossentropy: 0.1364 - sparse_categorical_accuracy: 0.9485 - scaled_adversarial_loss: 0.0932 - val_loss: 0.2478 - val_sparse_categorical_crossentropy: 0.1434 - val_sparse_categorical_accuracy: 0.9375 - val_scaled_adversarial_loss: 0.1044\n",
      "Epoch 242/1000\n",
      "11/11 [==============================] - 4s 331ms/step - loss: 0.2338 - sparse_categorical_crossentropy: 0.1424 - sparse_categorical_accuracy: 0.9457 - scaled_adversarial_loss: 0.0914 - val_loss: 0.2530 - val_sparse_categorical_crossentropy: 0.1427 - val_sparse_categorical_accuracy: 0.9413 - val_scaled_adversarial_loss: 0.1103\n",
      "Epoch 243/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.2300 - sparse_categorical_crossentropy: 0.1375 - sparse_categorical_accuracy: 0.9448 - scaled_adversarial_loss: 0.0925 - val_loss: 0.2481 - val_sparse_categorical_crossentropy: 0.1378 - val_sparse_categorical_accuracy: 0.9420 - val_scaled_adversarial_loss: 0.1103\n",
      "Epoch 244/1000\n",
      "11/11 [==============================] - 4s 329ms/step - loss: 0.2325 - sparse_categorical_crossentropy: 0.1422 - sparse_categorical_accuracy: 0.9470 - scaled_adversarial_loss: 0.0903 - val_loss: 0.2465 - val_sparse_categorical_crossentropy: 0.1409 - val_sparse_categorical_accuracy: 0.9390 - val_scaled_adversarial_loss: 0.1057\n",
      "Epoch 245/1000\n",
      "11/11 [==============================] - 4s 331ms/step - loss: 0.2314 - sparse_categorical_crossentropy: 0.1405 - sparse_categorical_accuracy: 0.9453 - scaled_adversarial_loss: 0.0909 - val_loss: 0.2436 - val_sparse_categorical_crossentropy: 0.1399 - val_sparse_categorical_accuracy: 0.9398 - val_scaled_adversarial_loss: 0.1037\n",
      "Epoch 246/1000\n",
      "11/11 [==============================] - 4s 332ms/step - loss: 0.2313 - sparse_categorical_crossentropy: 0.1398 - sparse_categorical_accuracy: 0.9464 - scaled_adversarial_loss: 0.0915 - val_loss: 0.2655 - val_sparse_categorical_crossentropy: 0.1498 - val_sparse_categorical_accuracy: 0.9405 - val_scaled_adversarial_loss: 0.1157\n",
      "Epoch 247/1000\n",
      "11/11 [==============================] - 4s 329ms/step - loss: 0.2300 - sparse_categorical_crossentropy: 0.1406 - sparse_categorical_accuracy: 0.9489 - scaled_adversarial_loss: 0.0894 - val_loss: 0.2579 - val_sparse_categorical_crossentropy: 0.1394 - val_sparse_categorical_accuracy: 0.9428 - val_scaled_adversarial_loss: 0.1186\n",
      "Epoch 248/1000\n",
      "11/11 [==============================] - 4s 332ms/step - loss: 0.2327 - sparse_categorical_crossentropy: 0.1387 - sparse_categorical_accuracy: 0.9483 - scaled_adversarial_loss: 0.0940 - val_loss: 0.2501 - val_sparse_categorical_crossentropy: 0.1445 - val_sparse_categorical_accuracy: 0.9375 - val_scaled_adversarial_loss: 0.1056\n",
      "Epoch 249/1000\n",
      "11/11 [==============================] - 4s 332ms/step - loss: 0.2382 - sparse_categorical_crossentropy: 0.1434 - sparse_categorical_accuracy: 0.9464 - scaled_adversarial_loss: 0.0948 - val_loss: 0.2447 - val_sparse_categorical_crossentropy: 0.1509 - val_sparse_categorical_accuracy: 0.9398 - val_scaled_adversarial_loss: 0.0938\n",
      "Epoch 250/1000\n",
      "11/11 [==============================] - 4s 330ms/step - loss: 0.2339 - sparse_categorical_crossentropy: 0.1449 - sparse_categorical_accuracy: 0.9463 - scaled_adversarial_loss: 0.0890 - val_loss: 0.2448 - val_sparse_categorical_crossentropy: 0.1451 - val_sparse_categorical_accuracy: 0.9450 - val_scaled_adversarial_loss: 0.0997\n",
      "Epoch 251/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.2277 - sparse_categorical_crossentropy: 0.1374 - sparse_categorical_accuracy: 0.9476 - scaled_adversarial_loss: 0.0902 - val_loss: 0.2503 - val_sparse_categorical_crossentropy: 0.1451 - val_sparse_categorical_accuracy: 0.9383 - val_scaled_adversarial_loss: 0.1052\n",
      "Epoch 252/1000\n",
      "11/11 [==============================] - 4s 329ms/step - loss: 0.2287 - sparse_categorical_crossentropy: 0.1377 - sparse_categorical_accuracy: 0.9461 - scaled_adversarial_loss: 0.0910 - val_loss: 0.2394 - val_sparse_categorical_crossentropy: 0.1363 - val_sparse_categorical_accuracy: 0.9442 - val_scaled_adversarial_loss: 0.1031\n",
      "Epoch 253/1000\n",
      "11/11 [==============================] - 4s 335ms/step - loss: 0.2256 - sparse_categorical_crossentropy: 0.1373 - sparse_categorical_accuracy: 0.9483 - scaled_adversarial_loss: 0.0883 - val_loss: 0.2504 - val_sparse_categorical_crossentropy: 0.1404 - val_sparse_categorical_accuracy: 0.9390 - val_scaled_adversarial_loss: 0.1099\n",
      "Epoch 254/1000\n",
      "11/11 [==============================] - 4s 328ms/step - loss: 0.2245 - sparse_categorical_crossentropy: 0.1344 - sparse_categorical_accuracy: 0.9463 - scaled_adversarial_loss: 0.0902 - val_loss: 0.2440 - val_sparse_categorical_crossentropy: 0.1432 - val_sparse_categorical_accuracy: 0.9390 - val_scaled_adversarial_loss: 0.1008\n",
      "Epoch 255/1000\n",
      "11/11 [==============================] - 4s 329ms/step - loss: 0.2233 - sparse_categorical_crossentropy: 0.1342 - sparse_categorical_accuracy: 0.9478 - scaled_adversarial_loss: 0.0891 - val_loss: 0.2396 - val_sparse_categorical_crossentropy: 0.1400 - val_sparse_categorical_accuracy: 0.9398 - val_scaled_adversarial_loss: 0.0996\n",
      "Epoch 256/1000\n",
      "11/11 [==============================] - 4s 339ms/step - loss: 0.2218 - sparse_categorical_crossentropy: 0.1338 - sparse_categorical_accuracy: 0.9494 - scaled_adversarial_loss: 0.0880 - val_loss: 0.2476 - val_sparse_categorical_crossentropy: 0.1394 - val_sparse_categorical_accuracy: 0.9413 - val_scaled_adversarial_loss: 0.1083\n",
      "Epoch 257/1000\n",
      "11/11 [==============================] - 4s 332ms/step - loss: 0.2175 - sparse_categorical_crossentropy: 0.1305 - sparse_categorical_accuracy: 0.9496 - scaled_adversarial_loss: 0.0870 - val_loss: 0.2426 - val_sparse_categorical_crossentropy: 0.1370 - val_sparse_categorical_accuracy: 0.9413 - val_scaled_adversarial_loss: 0.1056\n",
      "Epoch 258/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.2217 - sparse_categorical_crossentropy: 0.1334 - sparse_categorical_accuracy: 0.9479 - scaled_adversarial_loss: 0.0883 - val_loss: 0.2491 - val_sparse_categorical_crossentropy: 0.1389 - val_sparse_categorical_accuracy: 0.9428 - val_scaled_adversarial_loss: 0.1102\n",
      "Epoch 259/1000\n",
      "11/11 [==============================] - 4s 332ms/step - loss: 0.2220 - sparse_categorical_crossentropy: 0.1338 - sparse_categorical_accuracy: 0.9487 - scaled_adversarial_loss: 0.0882 - val_loss: 0.2366 - val_sparse_categorical_crossentropy: 0.1422 - val_sparse_categorical_accuracy: 0.9428 - val_scaled_adversarial_loss: 0.0943\n",
      "Epoch 260/1000\n",
      "11/11 [==============================] - 4s 331ms/step - loss: 0.2274 - sparse_categorical_crossentropy: 0.1397 - sparse_categorical_accuracy: 0.9468 - scaled_adversarial_loss: 0.0877 - val_loss: 0.2428 - val_sparse_categorical_crossentropy: 0.1414 - val_sparse_categorical_accuracy: 0.9368 - val_scaled_adversarial_loss: 0.1013\n",
      "Epoch 261/1000\n",
      "11/11 [==============================] - 4s 331ms/step - loss: 0.2226 - sparse_categorical_crossentropy: 0.1347 - sparse_categorical_accuracy: 0.9464 - scaled_adversarial_loss: 0.0879 - val_loss: 0.2359 - val_sparse_categorical_crossentropy: 0.1370 - val_sparse_categorical_accuracy: 0.9457 - val_scaled_adversarial_loss: 0.0989\n",
      "Epoch 262/1000\n",
      "11/11 [==============================] - 4s 331ms/step - loss: 0.2157 - sparse_categorical_crossentropy: 0.1296 - sparse_categorical_accuracy: 0.9511 - scaled_adversarial_loss: 0.0861 - val_loss: 0.2490 - val_sparse_categorical_crossentropy: 0.1349 - val_sparse_categorical_accuracy: 0.9465 - val_scaled_adversarial_loss: 0.1141\n",
      "Epoch 263/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.2184 - sparse_categorical_crossentropy: 0.1301 - sparse_categorical_accuracy: 0.9526 - scaled_adversarial_loss: 0.0883 - val_loss: 0.2400 - val_sparse_categorical_crossentropy: 0.1358 - val_sparse_categorical_accuracy: 0.9420 - val_scaled_adversarial_loss: 0.1042\n",
      "Epoch 264/1000\n",
      "11/11 [==============================] - 4s 335ms/step - loss: 0.2241 - sparse_categorical_crossentropy: 0.1357 - sparse_categorical_accuracy: 0.9492 - scaled_adversarial_loss: 0.0885 - val_loss: 0.2411 - val_sparse_categorical_crossentropy: 0.1322 - val_sparse_categorical_accuracy: 0.9457 - val_scaled_adversarial_loss: 0.1089\n",
      "Epoch 265/1000\n",
      "11/11 [==============================] - 4s 331ms/step - loss: 0.2183 - sparse_categorical_crossentropy: 0.1290 - sparse_categorical_accuracy: 0.9541 - scaled_adversarial_loss: 0.0892 - val_loss: 0.2452 - val_sparse_categorical_crossentropy: 0.1392 - val_sparse_categorical_accuracy: 0.9428 - val_scaled_adversarial_loss: 0.1060\n",
      "Epoch 266/1000\n",
      "11/11 [==============================] - 4s 332ms/step - loss: 0.2158 - sparse_categorical_crossentropy: 0.1276 - sparse_categorical_accuracy: 0.9522 - scaled_adversarial_loss: 0.0882 - val_loss: 0.2485 - val_sparse_categorical_crossentropy: 0.1381 - val_sparse_categorical_accuracy: 0.9420 - val_scaled_adversarial_loss: 0.1104\n",
      "Epoch 267/1000\n",
      "11/11 [==============================] - 4s 331ms/step - loss: 0.2151 - sparse_categorical_crossentropy: 0.1268 - sparse_categorical_accuracy: 0.9533 - scaled_adversarial_loss: 0.0883 - val_loss: 0.2551 - val_sparse_categorical_crossentropy: 0.1373 - val_sparse_categorical_accuracy: 0.9472 - val_scaled_adversarial_loss: 0.1178\n",
      "Epoch 268/1000\n",
      "11/11 [==============================] - 4s 331ms/step - loss: 0.2161 - sparse_categorical_crossentropy: 0.1286 - sparse_categorical_accuracy: 0.9513 - scaled_adversarial_loss: 0.0874 - val_loss: 0.2378 - val_sparse_categorical_crossentropy: 0.1388 - val_sparse_categorical_accuracy: 0.9405 - val_scaled_adversarial_loss: 0.0990\n",
      "Epoch 269/1000\n",
      "11/11 [==============================] - 4s 337ms/step - loss: 0.2158 - sparse_categorical_crossentropy: 0.1281 - sparse_categorical_accuracy: 0.9504 - scaled_adversarial_loss: 0.0877 - val_loss: 0.2367 - val_sparse_categorical_crossentropy: 0.1381 - val_sparse_categorical_accuracy: 0.9413 - val_scaled_adversarial_loss: 0.0987\n",
      "Epoch 270/1000\n",
      "11/11 [==============================] - 4s 331ms/step - loss: 0.2173 - sparse_categorical_crossentropy: 0.1299 - sparse_categorical_accuracy: 0.9517 - scaled_adversarial_loss: 0.0874 - val_loss: 0.2397 - val_sparse_categorical_crossentropy: 0.1376 - val_sparse_categorical_accuracy: 0.9428 - val_scaled_adversarial_loss: 0.1021\n",
      "Epoch 271/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.2189 - sparse_categorical_crossentropy: 0.1332 - sparse_categorical_accuracy: 0.9511 - scaled_adversarial_loss: 0.0857 - val_loss: 0.2365 - val_sparse_categorical_crossentropy: 0.1378 - val_sparse_categorical_accuracy: 0.9413 - val_scaled_adversarial_loss: 0.0986\n",
      "Epoch 272/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.2219 - sparse_categorical_crossentropy: 0.1339 - sparse_categorical_accuracy: 0.9496 - scaled_adversarial_loss: 0.0880 - val_loss: 0.2411 - val_sparse_categorical_crossentropy: 0.1384 - val_sparse_categorical_accuracy: 0.9398 - val_scaled_adversarial_loss: 0.1026\n",
      "Epoch 273/1000\n",
      "11/11 [==============================] - 4s 343ms/step - loss: 0.2147 - sparse_categorical_crossentropy: 0.1299 - sparse_categorical_accuracy: 0.9530 - scaled_adversarial_loss: 0.0849 - val_loss: 0.2361 - val_sparse_categorical_crossentropy: 0.1395 - val_sparse_categorical_accuracy: 0.9413 - val_scaled_adversarial_loss: 0.0966\n",
      "Epoch 274/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.2102 - sparse_categorical_crossentropy: 0.1261 - sparse_categorical_accuracy: 0.9541 - scaled_adversarial_loss: 0.0841 - val_loss: 0.2350 - val_sparse_categorical_crossentropy: 0.1335 - val_sparse_categorical_accuracy: 0.9435 - val_scaled_adversarial_loss: 0.1015\n",
      "Epoch 275/1000\n",
      "11/11 [==============================] - 4s 331ms/step - loss: 0.2121 - sparse_categorical_crossentropy: 0.1239 - sparse_categorical_accuracy: 0.9533 - scaled_adversarial_loss: 0.0882 - val_loss: 0.2516 - val_sparse_categorical_crossentropy: 0.1348 - val_sparse_categorical_accuracy: 0.9398 - val_scaled_adversarial_loss: 0.1168\n",
      "Epoch 276/1000\n",
      "11/11 [==============================] - 4s 331ms/step - loss: 0.2194 - sparse_categorical_crossentropy: 0.1310 - sparse_categorical_accuracy: 0.9505 - scaled_adversarial_loss: 0.0884 - val_loss: 0.2491 - val_sparse_categorical_crossentropy: 0.1350 - val_sparse_categorical_accuracy: 0.9413 - val_scaled_adversarial_loss: 0.1141\n",
      "Epoch 277/1000\n",
      "11/11 [==============================] - 4s 332ms/step - loss: 0.2162 - sparse_categorical_crossentropy: 0.1277 - sparse_categorical_accuracy: 0.9485 - scaled_adversarial_loss: 0.0885 - val_loss: 0.2486 - val_sparse_categorical_crossentropy: 0.1354 - val_sparse_categorical_accuracy: 0.9465 - val_scaled_adversarial_loss: 0.1132\n",
      "Epoch 278/1000\n",
      "11/11 [==============================] - 4s 335ms/step - loss: 0.2143 - sparse_categorical_crossentropy: 0.1290 - sparse_categorical_accuracy: 0.9522 - scaled_adversarial_loss: 0.0853 - val_loss: 0.2430 - val_sparse_categorical_crossentropy: 0.1337 - val_sparse_categorical_accuracy: 0.9420 - val_scaled_adversarial_loss: 0.1093\n",
      "Epoch 279/1000\n",
      "11/11 [==============================] - 4s 331ms/step - loss: 0.2152 - sparse_categorical_crossentropy: 0.1259 - sparse_categorical_accuracy: 0.9498 - scaled_adversarial_loss: 0.0894 - val_loss: 0.2468 - val_sparse_categorical_crossentropy: 0.1356 - val_sparse_categorical_accuracy: 0.9413 - val_scaled_adversarial_loss: 0.1112\n",
      "Epoch 280/1000\n",
      "11/11 [==============================] - 4s 337ms/step - loss: 0.2183 - sparse_categorical_crossentropy: 0.1316 - sparse_categorical_accuracy: 0.9502 - scaled_adversarial_loss: 0.0867 - val_loss: 0.2437 - val_sparse_categorical_crossentropy: 0.1338 - val_sparse_categorical_accuracy: 0.9428 - val_scaled_adversarial_loss: 0.1099\n",
      "Epoch 281/1000\n",
      "11/11 [==============================] - 4s 336ms/step - loss: 0.2124 - sparse_categorical_crossentropy: 0.1274 - sparse_categorical_accuracy: 0.9524 - scaled_adversarial_loss: 0.0850 - val_loss: 0.2370 - val_sparse_categorical_crossentropy: 0.1349 - val_sparse_categorical_accuracy: 0.9435 - val_scaled_adversarial_loss: 0.1021\n",
      "Epoch 282/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.2228 - sparse_categorical_crossentropy: 0.1331 - sparse_categorical_accuracy: 0.9498 - scaled_adversarial_loss: 0.0897 - val_loss: 0.2416 - val_sparse_categorical_crossentropy: 0.1380 - val_sparse_categorical_accuracy: 0.9413 - val_scaled_adversarial_loss: 0.1036\n",
      "Epoch 283/1000\n",
      "11/11 [==============================] - 4s 340ms/step - loss: 0.2169 - sparse_categorical_crossentropy: 0.1281 - sparse_categorical_accuracy: 0.9528 - scaled_adversarial_loss: 0.0889 - val_loss: 0.2414 - val_sparse_categorical_crossentropy: 0.1436 - val_sparse_categorical_accuracy: 0.9450 - val_scaled_adversarial_loss: 0.0978\n",
      "Epoch 284/1000\n",
      "11/11 [==============================] - 4s 336ms/step - loss: 0.2242 - sparse_categorical_crossentropy: 0.1343 - sparse_categorical_accuracy: 0.9524 - scaled_adversarial_loss: 0.0899 - val_loss: 0.2353 - val_sparse_categorical_crossentropy: 0.1362 - val_sparse_categorical_accuracy: 0.9390 - val_scaled_adversarial_loss: 0.0992\n",
      "Epoch 285/1000\n",
      "11/11 [==============================] - 4s 337ms/step - loss: 0.2158 - sparse_categorical_crossentropy: 0.1264 - sparse_categorical_accuracy: 0.9537 - scaled_adversarial_loss: 0.0894 - val_loss: 0.2367 - val_sparse_categorical_crossentropy: 0.1320 - val_sparse_categorical_accuracy: 0.9472 - val_scaled_adversarial_loss: 0.1047\n",
      "Epoch 286/1000\n",
      "11/11 [==============================] - 4s 332ms/step - loss: 0.2174 - sparse_categorical_crossentropy: 0.1315 - sparse_categorical_accuracy: 0.9511 - scaled_adversarial_loss: 0.0859 - val_loss: 0.2396 - val_sparse_categorical_crossentropy: 0.1336 - val_sparse_categorical_accuracy: 0.9450 - val_scaled_adversarial_loss: 0.1061\n",
      "Epoch 287/1000\n",
      "11/11 [==============================] - 4s 335ms/step - loss: 0.2087 - sparse_categorical_crossentropy: 0.1251 - sparse_categorical_accuracy: 0.9524 - scaled_adversarial_loss: 0.0836 - val_loss: 0.2441 - val_sparse_categorical_crossentropy: 0.1296 - val_sparse_categorical_accuracy: 0.9428 - val_scaled_adversarial_loss: 0.1145\n",
      "Epoch 288/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.2140 - sparse_categorical_crossentropy: 0.1274 - sparse_categorical_accuracy: 0.9524 - scaled_adversarial_loss: 0.0866 - val_loss: 0.2444 - val_sparse_categorical_crossentropy: 0.1306 - val_sparse_categorical_accuracy: 0.9465 - val_scaled_adversarial_loss: 0.1138\n",
      "Epoch 289/1000\n",
      "11/11 [==============================] - 4s 335ms/step - loss: 0.2100 - sparse_categorical_crossentropy: 0.1224 - sparse_categorical_accuracy: 0.9528 - scaled_adversarial_loss: 0.0876 - val_loss: 0.2348 - val_sparse_categorical_crossentropy: 0.1333 - val_sparse_categorical_accuracy: 0.9465 - val_scaled_adversarial_loss: 0.1015\n",
      "Epoch 290/1000\n",
      "11/11 [==============================] - 4s 332ms/step - loss: 0.2093 - sparse_categorical_crossentropy: 0.1247 - sparse_categorical_accuracy: 0.9518 - scaled_adversarial_loss: 0.0846 - val_loss: 0.2319 - val_sparse_categorical_crossentropy: 0.1339 - val_sparse_categorical_accuracy: 0.9450 - val_scaled_adversarial_loss: 0.0980\n",
      "Epoch 291/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.2057 - sparse_categorical_crossentropy: 0.1206 - sparse_categorical_accuracy: 0.9539 - scaled_adversarial_loss: 0.0851 - val_loss: 0.2392 - val_sparse_categorical_crossentropy: 0.1314 - val_sparse_categorical_accuracy: 0.9465 - val_scaled_adversarial_loss: 0.1078\n",
      "Epoch 292/1000\n",
      "11/11 [==============================] - 4s 332ms/step - loss: 0.2067 - sparse_categorical_crossentropy: 0.1232 - sparse_categorical_accuracy: 0.9561 - scaled_adversarial_loss: 0.0835 - val_loss: 0.2448 - val_sparse_categorical_crossentropy: 0.1339 - val_sparse_categorical_accuracy: 0.9413 - val_scaled_adversarial_loss: 0.1109\n",
      "Epoch 293/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.2136 - sparse_categorical_crossentropy: 0.1277 - sparse_categorical_accuracy: 0.9528 - scaled_adversarial_loss: 0.0860 - val_loss: 0.2372 - val_sparse_categorical_crossentropy: 0.1424 - val_sparse_categorical_accuracy: 0.9368 - val_scaled_adversarial_loss: 0.0948\n",
      "Epoch 294/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.2130 - sparse_categorical_crossentropy: 0.1250 - sparse_categorical_accuracy: 0.9496 - scaled_adversarial_loss: 0.0880 - val_loss: 0.2686 - val_sparse_categorical_crossentropy: 0.1434 - val_sparse_categorical_accuracy: 0.9405 - val_scaled_adversarial_loss: 0.1252\n",
      "Epoch 295/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.2111 - sparse_categorical_crossentropy: 0.1224 - sparse_categorical_accuracy: 0.9539 - scaled_adversarial_loss: 0.0887 - val_loss: 0.2399 - val_sparse_categorical_crossentropy: 0.1387 - val_sparse_categorical_accuracy: 0.9375 - val_scaled_adversarial_loss: 0.1012\n",
      "Epoch 296/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.2162 - sparse_categorical_crossentropy: 0.1278 - sparse_categorical_accuracy: 0.9530 - scaled_adversarial_loss: 0.0883 - val_loss: 0.2443 - val_sparse_categorical_crossentropy: 0.1343 - val_sparse_categorical_accuracy: 0.9420 - val_scaled_adversarial_loss: 0.1100\n",
      "Epoch 297/1000\n",
      "11/11 [==============================] - 4s 335ms/step - loss: 0.2090 - sparse_categorical_crossentropy: 0.1243 - sparse_categorical_accuracy: 0.9520 - scaled_adversarial_loss: 0.0847 - val_loss: 0.2438 - val_sparse_categorical_crossentropy: 0.1312 - val_sparse_categorical_accuracy: 0.9450 - val_scaled_adversarial_loss: 0.1127\n",
      "Epoch 298/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.2114 - sparse_categorical_crossentropy: 0.1245 - sparse_categorical_accuracy: 0.9528 - scaled_adversarial_loss: 0.0869 - val_loss: 0.2400 - val_sparse_categorical_crossentropy: 0.1327 - val_sparse_categorical_accuracy: 0.9457 - val_scaled_adversarial_loss: 0.1073\n",
      "Epoch 299/1000\n",
      "11/11 [==============================] - 4s 335ms/step - loss: 0.2026 - sparse_categorical_crossentropy: 0.1191 - sparse_categorical_accuracy: 0.9544 - scaled_adversarial_loss: 0.0834 - val_loss: 0.2387 - val_sparse_categorical_crossentropy: 0.1319 - val_sparse_categorical_accuracy: 0.9428 - val_scaled_adversarial_loss: 0.1068\n",
      "Epoch 300/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.2082 - sparse_categorical_crossentropy: 0.1220 - sparse_categorical_accuracy: 0.9550 - scaled_adversarial_loss: 0.0863 - val_loss: 0.2340 - val_sparse_categorical_crossentropy: 0.1237 - val_sparse_categorical_accuracy: 0.9457 - val_scaled_adversarial_loss: 0.1104\n",
      "Epoch 301/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.2083 - sparse_categorical_crossentropy: 0.1225 - sparse_categorical_accuracy: 0.9535 - scaled_adversarial_loss: 0.0858 - val_loss: 0.2250 - val_sparse_categorical_crossentropy: 0.1280 - val_sparse_categorical_accuracy: 0.9472 - val_scaled_adversarial_loss: 0.0969\n",
      "Epoch 302/1000\n",
      "11/11 [==============================] - 4s 332ms/step - loss: 0.1972 - sparse_categorical_crossentropy: 0.1158 - sparse_categorical_accuracy: 0.9572 - scaled_adversarial_loss: 0.0814 - val_loss: 0.2533 - val_sparse_categorical_crossentropy: 0.1393 - val_sparse_categorical_accuracy: 0.9450 - val_scaled_adversarial_loss: 0.1139\n",
      "Epoch 303/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.2133 - sparse_categorical_crossentropy: 0.1223 - sparse_categorical_accuracy: 0.9546 - scaled_adversarial_loss: 0.0911 - val_loss: 0.2584 - val_sparse_categorical_crossentropy: 0.1376 - val_sparse_categorical_accuracy: 0.9472 - val_scaled_adversarial_loss: 0.1209\n",
      "Epoch 304/1000\n",
      "11/11 [==============================] - 4s 331ms/step - loss: 0.2076 - sparse_categorical_crossentropy: 0.1183 - sparse_categorical_accuracy: 0.9526 - scaled_adversarial_loss: 0.0893 - val_loss: 0.2351 - val_sparse_categorical_crossentropy: 0.1280 - val_sparse_categorical_accuracy: 0.9472 - val_scaled_adversarial_loss: 0.1071\n",
      "Epoch 305/1000\n",
      "11/11 [==============================] - 4s 339ms/step - loss: 0.2108 - sparse_categorical_crossentropy: 0.1258 - sparse_categorical_accuracy: 0.9500 - scaled_adversarial_loss: 0.0850 - val_loss: 0.2342 - val_sparse_categorical_crossentropy: 0.1261 - val_sparse_categorical_accuracy: 0.9450 - val_scaled_adversarial_loss: 0.1081\n",
      "Epoch 306/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.2083 - sparse_categorical_crossentropy: 0.1230 - sparse_categorical_accuracy: 0.9533 - scaled_adversarial_loss: 0.0853 - val_loss: 0.2264 - val_sparse_categorical_crossentropy: 0.1270 - val_sparse_categorical_accuracy: 0.9465 - val_scaled_adversarial_loss: 0.0995\n",
      "Epoch 307/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.2038 - sparse_categorical_crossentropy: 0.1209 - sparse_categorical_accuracy: 0.9561 - scaled_adversarial_loss: 0.0829 - val_loss: 0.2385 - val_sparse_categorical_crossentropy: 0.1342 - val_sparse_categorical_accuracy: 0.9457 - val_scaled_adversarial_loss: 0.1043\n",
      "Epoch 308/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.2034 - sparse_categorical_crossentropy: 0.1207 - sparse_categorical_accuracy: 0.9550 - scaled_adversarial_loss: 0.0827 - val_loss: 0.2329 - val_sparse_categorical_crossentropy: 0.1347 - val_sparse_categorical_accuracy: 0.9450 - val_scaled_adversarial_loss: 0.0982\n",
      "Epoch 309/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.2012 - sparse_categorical_crossentropy: 0.1181 - sparse_categorical_accuracy: 0.9535 - scaled_adversarial_loss: 0.0831 - val_loss: 0.2458 - val_sparse_categorical_crossentropy: 0.1352 - val_sparse_categorical_accuracy: 0.9428 - val_scaled_adversarial_loss: 0.1106\n",
      "Epoch 310/1000\n",
      "11/11 [==============================] - 4s 332ms/step - loss: 0.2127 - sparse_categorical_crossentropy: 0.1261 - sparse_categorical_accuracy: 0.9533 - scaled_adversarial_loss: 0.0865 - val_loss: 0.2598 - val_sparse_categorical_crossentropy: 0.1380 - val_sparse_categorical_accuracy: 0.9487 - val_scaled_adversarial_loss: 0.1217\n",
      "Epoch 311/1000\n",
      "11/11 [==============================] - 4s 335ms/step - loss: 0.2088 - sparse_categorical_crossentropy: 0.1214 - sparse_categorical_accuracy: 0.9544 - scaled_adversarial_loss: 0.0874 - val_loss: 0.2428 - val_sparse_categorical_crossentropy: 0.1294 - val_sparse_categorical_accuracy: 0.9435 - val_scaled_adversarial_loss: 0.1134\n",
      "Epoch 312/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.2066 - sparse_categorical_crossentropy: 0.1214 - sparse_categorical_accuracy: 0.9526 - scaled_adversarial_loss: 0.0852 - val_loss: 0.2331 - val_sparse_categorical_crossentropy: 0.1292 - val_sparse_categorical_accuracy: 0.9457 - val_scaled_adversarial_loss: 0.1039\n",
      "Epoch 313/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.1999 - sparse_categorical_crossentropy: 0.1154 - sparse_categorical_accuracy: 0.9541 - scaled_adversarial_loss: 0.0844 - val_loss: 0.2369 - val_sparse_categorical_crossentropy: 0.1278 - val_sparse_categorical_accuracy: 0.9494 - val_scaled_adversarial_loss: 0.1091\n",
      "Epoch 314/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.1977 - sparse_categorical_crossentropy: 0.1143 - sparse_categorical_accuracy: 0.9569 - scaled_adversarial_loss: 0.0835 - val_loss: 0.2391 - val_sparse_categorical_crossentropy: 0.1313 - val_sparse_categorical_accuracy: 0.9450 - val_scaled_adversarial_loss: 0.1078\n",
      "Epoch 315/1000\n",
      "11/11 [==============================] - 4s 332ms/step - loss: 0.2045 - sparse_categorical_crossentropy: 0.1201 - sparse_categorical_accuracy: 0.9559 - scaled_adversarial_loss: 0.0844 - val_loss: 0.2254 - val_sparse_categorical_crossentropy: 0.1266 - val_sparse_categorical_accuracy: 0.9494 - val_scaled_adversarial_loss: 0.0987\n",
      "Epoch 316/1000\n",
      "11/11 [==============================] - 4s 331ms/step - loss: 0.2091 - sparse_categorical_crossentropy: 0.1249 - sparse_categorical_accuracy: 0.9561 - scaled_adversarial_loss: 0.0842 - val_loss: 0.2460 - val_sparse_categorical_crossentropy: 0.1335 - val_sparse_categorical_accuracy: 0.9435 - val_scaled_adversarial_loss: 0.1125\n",
      "Epoch 317/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.1967 - sparse_categorical_crossentropy: 0.1123 - sparse_categorical_accuracy: 0.9583 - scaled_adversarial_loss: 0.0844 - val_loss: 0.2621 - val_sparse_categorical_crossentropy: 0.1423 - val_sparse_categorical_accuracy: 0.9502 - val_scaled_adversarial_loss: 0.1198\n",
      "Epoch 318/1000\n",
      "11/11 [==============================] - 4s 335ms/step - loss: 0.1988 - sparse_categorical_crossentropy: 0.1168 - sparse_categorical_accuracy: 0.9561 - scaled_adversarial_loss: 0.0820 - val_loss: 0.2338 - val_sparse_categorical_crossentropy: 0.1288 - val_sparse_categorical_accuracy: 0.9480 - val_scaled_adversarial_loss: 0.1050\n",
      "Epoch 319/1000\n",
      "11/11 [==============================] - 4s 335ms/step - loss: 0.1970 - sparse_categorical_crossentropy: 0.1155 - sparse_categorical_accuracy: 0.9563 - scaled_adversarial_loss: 0.0815 - val_loss: 0.2300 - val_sparse_categorical_crossentropy: 0.1268 - val_sparse_categorical_accuracy: 0.9480 - val_scaled_adversarial_loss: 0.1032\n",
      "Epoch 320/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.1984 - sparse_categorical_crossentropy: 0.1159 - sparse_categorical_accuracy: 0.9565 - scaled_adversarial_loss: 0.0825 - val_loss: 0.2399 - val_sparse_categorical_crossentropy: 0.1287 - val_sparse_categorical_accuracy: 0.9428 - val_scaled_adversarial_loss: 0.1112\n",
      "Epoch 321/1000\n",
      "11/11 [==============================] - 4s 335ms/step - loss: 0.1960 - sparse_categorical_crossentropy: 0.1125 - sparse_categorical_accuracy: 0.9587 - scaled_adversarial_loss: 0.0836 - val_loss: 0.2254 - val_sparse_categorical_crossentropy: 0.1277 - val_sparse_categorical_accuracy: 0.9480 - val_scaled_adversarial_loss: 0.0977\n",
      "Epoch 322/1000\n",
      "11/11 [==============================] - 4s 331ms/step - loss: 0.1971 - sparse_categorical_crossentropy: 0.1126 - sparse_categorical_accuracy: 0.9611 - scaled_adversarial_loss: 0.0846 - val_loss: 0.2374 - val_sparse_categorical_crossentropy: 0.1332 - val_sparse_categorical_accuracy: 0.9450 - val_scaled_adversarial_loss: 0.1041\n",
      "Epoch 323/1000\n",
      "11/11 [==============================] - 4s 335ms/step - loss: 0.1965 - sparse_categorical_crossentropy: 0.1117 - sparse_categorical_accuracy: 0.9583 - scaled_adversarial_loss: 0.0847 - val_loss: 0.2380 - val_sparse_categorical_crossentropy: 0.1312 - val_sparse_categorical_accuracy: 0.9465 - val_scaled_adversarial_loss: 0.1068\n",
      "Epoch 324/1000\n",
      "11/11 [==============================] - 4s 332ms/step - loss: 0.1996 - sparse_categorical_crossentropy: 0.1151 - sparse_categorical_accuracy: 0.9572 - scaled_adversarial_loss: 0.0845 - val_loss: 0.2287 - val_sparse_categorical_crossentropy: 0.1316 - val_sparse_categorical_accuracy: 0.9465 - val_scaled_adversarial_loss: 0.0971\n",
      "Epoch 325/1000\n",
      "11/11 [==============================] - 4s 332ms/step - loss: 0.2015 - sparse_categorical_crossentropy: 0.1172 - sparse_categorical_accuracy: 0.9567 - scaled_adversarial_loss: 0.0843 - val_loss: 0.2209 - val_sparse_categorical_crossentropy: 0.1287 - val_sparse_categorical_accuracy: 0.9480 - val_scaled_adversarial_loss: 0.0922\n",
      "Epoch 326/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.2055 - sparse_categorical_crossentropy: 0.1213 - sparse_categorical_accuracy: 0.9543 - scaled_adversarial_loss: 0.0842 - val_loss: 0.2237 - val_sparse_categorical_crossentropy: 0.1289 - val_sparse_categorical_accuracy: 0.9457 - val_scaled_adversarial_loss: 0.0948\n",
      "Epoch 327/1000\n",
      "11/11 [==============================] - 4s 338ms/step - loss: 0.1973 - sparse_categorical_crossentropy: 0.1150 - sparse_categorical_accuracy: 0.9583 - scaled_adversarial_loss: 0.0823 - val_loss: 0.2326 - val_sparse_categorical_crossentropy: 0.1298 - val_sparse_categorical_accuracy: 0.9450 - val_scaled_adversarial_loss: 0.1028\n",
      "Epoch 328/1000\n",
      "11/11 [==============================] - 4s 338ms/step - loss: 0.1905 - sparse_categorical_crossentropy: 0.1110 - sparse_categorical_accuracy: 0.9569 - scaled_adversarial_loss: 0.0795 - val_loss: 0.2413 - val_sparse_categorical_crossentropy: 0.1316 - val_sparse_categorical_accuracy: 0.9472 - val_scaled_adversarial_loss: 0.1098\n",
      "Epoch 329/1000\n",
      "11/11 [==============================] - 4s 335ms/step - loss: 0.1974 - sparse_categorical_crossentropy: 0.1111 - sparse_categorical_accuracy: 0.9565 - scaled_adversarial_loss: 0.0863 - val_loss: 0.2473 - val_sparse_categorical_crossentropy: 0.1301 - val_sparse_categorical_accuracy: 0.9494 - val_scaled_adversarial_loss: 0.1172\n",
      "Epoch 330/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.1956 - sparse_categorical_crossentropy: 0.1125 - sparse_categorical_accuracy: 0.9559 - scaled_adversarial_loss: 0.0831 - val_loss: 0.2538 - val_sparse_categorical_crossentropy: 0.1395 - val_sparse_categorical_accuracy: 0.9457 - val_scaled_adversarial_loss: 0.1143\n",
      "Epoch 331/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.1981 - sparse_categorical_crossentropy: 0.1138 - sparse_categorical_accuracy: 0.9587 - scaled_adversarial_loss: 0.0843 - val_loss: 0.2270 - val_sparse_categorical_crossentropy: 0.1244 - val_sparse_categorical_accuracy: 0.9442 - val_scaled_adversarial_loss: 0.1025\n",
      "Epoch 332/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.1980 - sparse_categorical_crossentropy: 0.1161 - sparse_categorical_accuracy: 0.9578 - scaled_adversarial_loss: 0.0819 - val_loss: 0.2219 - val_sparse_categorical_crossentropy: 0.1272 - val_sparse_categorical_accuracy: 0.9442 - val_scaled_adversarial_loss: 0.0947\n",
      "Epoch 333/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.2012 - sparse_categorical_crossentropy: 0.1184 - sparse_categorical_accuracy: 0.9567 - scaled_adversarial_loss: 0.0827 - val_loss: 0.2441 - val_sparse_categorical_crossentropy: 0.1327 - val_sparse_categorical_accuracy: 0.9494 - val_scaled_adversarial_loss: 0.1114\n",
      "Epoch 334/1000\n",
      "11/11 [==============================] - 4s 336ms/step - loss: 0.2030 - sparse_categorical_crossentropy: 0.1185 - sparse_categorical_accuracy: 0.9563 - scaled_adversarial_loss: 0.0845 - val_loss: 0.2424 - val_sparse_categorical_crossentropy: 0.1313 - val_sparse_categorical_accuracy: 0.9457 - val_scaled_adversarial_loss: 0.1111\n",
      "Epoch 335/1000\n",
      "11/11 [==============================] - 4s 336ms/step - loss: 0.2059 - sparse_categorical_crossentropy: 0.1217 - sparse_categorical_accuracy: 0.9563 - scaled_adversarial_loss: 0.0841 - val_loss: 0.2236 - val_sparse_categorical_crossentropy: 0.1330 - val_sparse_categorical_accuracy: 0.9457 - val_scaled_adversarial_loss: 0.0905\n",
      "Epoch 336/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.1948 - sparse_categorical_crossentropy: 0.1119 - sparse_categorical_accuracy: 0.9591 - scaled_adversarial_loss: 0.0829 - val_loss: 0.2238 - val_sparse_categorical_crossentropy: 0.1291 - val_sparse_categorical_accuracy: 0.9480 - val_scaled_adversarial_loss: 0.0947\n",
      "Epoch 337/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.1939 - sparse_categorical_crossentropy: 0.1124 - sparse_categorical_accuracy: 0.9569 - scaled_adversarial_loss: 0.0816 - val_loss: 0.2269 - val_sparse_categorical_crossentropy: 0.1250 - val_sparse_categorical_accuracy: 0.9517 - val_scaled_adversarial_loss: 0.1019\n",
      "Epoch 338/1000\n",
      "11/11 [==============================] - 4s 338ms/step - loss: 0.1916 - sparse_categorical_crossentropy: 0.1106 - sparse_categorical_accuracy: 0.9583 - scaled_adversarial_loss: 0.0810 - val_loss: 0.2342 - val_sparse_categorical_crossentropy: 0.1332 - val_sparse_categorical_accuracy: 0.9450 - val_scaled_adversarial_loss: 0.1010\n",
      "Epoch 339/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.1950 - sparse_categorical_crossentropy: 0.1105 - sparse_categorical_accuracy: 0.9574 - scaled_adversarial_loss: 0.0846 - val_loss: 0.2314 - val_sparse_categorical_crossentropy: 0.1283 - val_sparse_categorical_accuracy: 0.9450 - val_scaled_adversarial_loss: 0.1032\n",
      "Epoch 340/1000\n",
      "11/11 [==============================] - 4s 337ms/step - loss: 0.1927 - sparse_categorical_crossentropy: 0.1132 - sparse_categorical_accuracy: 0.9574 - scaled_adversarial_loss: 0.0795 - val_loss: 0.2268 - val_sparse_categorical_crossentropy: 0.1317 - val_sparse_categorical_accuracy: 0.9465 - val_scaled_adversarial_loss: 0.0950\n",
      "Epoch 341/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.1944 - sparse_categorical_crossentropy: 0.1154 - sparse_categorical_accuracy: 0.9554 - scaled_adversarial_loss: 0.0789 - val_loss: 0.2216 - val_sparse_categorical_crossentropy: 0.1256 - val_sparse_categorical_accuracy: 0.9472 - val_scaled_adversarial_loss: 0.0959\n",
      "Epoch 342/1000\n",
      "11/11 [==============================] - 4s 331ms/step - loss: 0.1996 - sparse_categorical_crossentropy: 0.1179 - sparse_categorical_accuracy: 0.9546 - scaled_adversarial_loss: 0.0817 - val_loss: 0.2264 - val_sparse_categorical_crossentropy: 0.1320 - val_sparse_categorical_accuracy: 0.9457 - val_scaled_adversarial_loss: 0.0944\n",
      "Epoch 343/1000\n",
      "11/11 [==============================] - 4s 335ms/step - loss: 0.1925 - sparse_categorical_crossentropy: 0.1110 - sparse_categorical_accuracy: 0.9576 - scaled_adversarial_loss: 0.0814 - val_loss: 0.2291 - val_sparse_categorical_crossentropy: 0.1251 - val_sparse_categorical_accuracy: 0.9457 - val_scaled_adversarial_loss: 0.1040\n",
      "Epoch 344/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.1871 - sparse_categorical_crossentropy: 0.1061 - sparse_categorical_accuracy: 0.9608 - scaled_adversarial_loss: 0.0810 - val_loss: 0.2269 - val_sparse_categorical_crossentropy: 0.1263 - val_sparse_categorical_accuracy: 0.9487 - val_scaled_adversarial_loss: 0.1005\n",
      "Epoch 345/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.1957 - sparse_categorical_crossentropy: 0.1106 - sparse_categorical_accuracy: 0.9570 - scaled_adversarial_loss: 0.0850 - val_loss: 0.2419 - val_sparse_categorical_crossentropy: 0.1334 - val_sparse_categorical_accuracy: 0.9480 - val_scaled_adversarial_loss: 0.1085\n",
      "Epoch 346/1000\n",
      "11/11 [==============================] - 4s 337ms/step - loss: 0.1997 - sparse_categorical_crossentropy: 0.1149 - sparse_categorical_accuracy: 0.9585 - scaled_adversarial_loss: 0.0848 - val_loss: 0.2168 - val_sparse_categorical_crossentropy: 0.1313 - val_sparse_categorical_accuracy: 0.9494 - val_scaled_adversarial_loss: 0.0855\n",
      "Epoch 347/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.2001 - sparse_categorical_crossentropy: 0.1187 - sparse_categorical_accuracy: 0.9593 - scaled_adversarial_loss: 0.0814 - val_loss: 0.2239 - val_sparse_categorical_crossentropy: 0.1277 - val_sparse_categorical_accuracy: 0.9494 - val_scaled_adversarial_loss: 0.0962\n",
      "Epoch 348/1000\n",
      "11/11 [==============================] - 4s 340ms/step - loss: 0.1937 - sparse_categorical_crossentropy: 0.1111 - sparse_categorical_accuracy: 0.9565 - scaled_adversarial_loss: 0.0825 - val_loss: 0.2300 - val_sparse_categorical_crossentropy: 0.1258 - val_sparse_categorical_accuracy: 0.9487 - val_scaled_adversarial_loss: 0.1042\n",
      "Epoch 349/1000\n",
      "11/11 [==============================] - 4s 335ms/step - loss: 0.1919 - sparse_categorical_crossentropy: 0.1064 - sparse_categorical_accuracy: 0.9604 - scaled_adversarial_loss: 0.0855 - val_loss: 0.2223 - val_sparse_categorical_crossentropy: 0.1243 - val_sparse_categorical_accuracy: 0.9472 - val_scaled_adversarial_loss: 0.0979\n",
      "Epoch 350/1000\n",
      "11/11 [==============================] - 4s 335ms/step - loss: 0.1889 - sparse_categorical_crossentropy: 0.1107 - sparse_categorical_accuracy: 0.9589 - scaled_adversarial_loss: 0.0783 - val_loss: 0.2195 - val_sparse_categorical_crossentropy: 0.1255 - val_sparse_categorical_accuracy: 0.9524 - val_scaled_adversarial_loss: 0.0939\n",
      "Epoch 351/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.1925 - sparse_categorical_crossentropy: 0.1131 - sparse_categorical_accuracy: 0.9582 - scaled_adversarial_loss: 0.0794 - val_loss: 0.2238 - val_sparse_categorical_crossentropy: 0.1244 - val_sparse_categorical_accuracy: 0.9502 - val_scaled_adversarial_loss: 0.0994\n",
      "Epoch 352/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.1862 - sparse_categorical_crossentropy: 0.1056 - sparse_categorical_accuracy: 0.9602 - scaled_adversarial_loss: 0.0806 - val_loss: 0.2371 - val_sparse_categorical_crossentropy: 0.1333 - val_sparse_categorical_accuracy: 0.9480 - val_scaled_adversarial_loss: 0.1038\n",
      "Epoch 353/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.1891 - sparse_categorical_crossentropy: 0.1080 - sparse_categorical_accuracy: 0.9580 - scaled_adversarial_loss: 0.0811 - val_loss: 0.2128 - val_sparse_categorical_crossentropy: 0.1272 - val_sparse_categorical_accuracy: 0.9494 - val_scaled_adversarial_loss: 0.0856\n",
      "Epoch 354/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.1934 - sparse_categorical_crossentropy: 0.1114 - sparse_categorical_accuracy: 0.9572 - scaled_adversarial_loss: 0.0820 - val_loss: 0.2404 - val_sparse_categorical_crossentropy: 0.1372 - val_sparse_categorical_accuracy: 0.9435 - val_scaled_adversarial_loss: 0.1032\n",
      "Epoch 355/1000\n",
      "11/11 [==============================] - 4s 336ms/step - loss: 0.1922 - sparse_categorical_crossentropy: 0.1099 - sparse_categorical_accuracy: 0.9580 - scaled_adversarial_loss: 0.0824 - val_loss: 0.2184 - val_sparse_categorical_crossentropy: 0.1232 - val_sparse_categorical_accuracy: 0.9524 - val_scaled_adversarial_loss: 0.0952\n",
      "Epoch 356/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.1852 - sparse_categorical_crossentropy: 0.1049 - sparse_categorical_accuracy: 0.9597 - scaled_adversarial_loss: 0.0803 - val_loss: 0.2185 - val_sparse_categorical_crossentropy: 0.1232 - val_sparse_categorical_accuracy: 0.9517 - val_scaled_adversarial_loss: 0.0952\n",
      "Epoch 357/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.1897 - sparse_categorical_crossentropy: 0.1106 - sparse_categorical_accuracy: 0.9613 - scaled_adversarial_loss: 0.0791 - val_loss: 0.2186 - val_sparse_categorical_crossentropy: 0.1192 - val_sparse_categorical_accuracy: 0.9524 - val_scaled_adversarial_loss: 0.0994\n",
      "Epoch 358/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.1903 - sparse_categorical_crossentropy: 0.1102 - sparse_categorical_accuracy: 0.9589 - scaled_adversarial_loss: 0.0801 - val_loss: 0.2240 - val_sparse_categorical_crossentropy: 0.1248 - val_sparse_categorical_accuracy: 0.9480 - val_scaled_adversarial_loss: 0.0992\n",
      "Epoch 359/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.1914 - sparse_categorical_crossentropy: 0.1104 - sparse_categorical_accuracy: 0.9578 - scaled_adversarial_loss: 0.0809 - val_loss: 0.2414 - val_sparse_categorical_crossentropy: 0.1294 - val_sparse_categorical_accuracy: 0.9457 - val_scaled_adversarial_loss: 0.1120\n",
      "Epoch 360/1000\n",
      "11/11 [==============================] - 4s 331ms/step - loss: 0.1812 - sparse_categorical_crossentropy: 0.1009 - sparse_categorical_accuracy: 0.9623 - scaled_adversarial_loss: 0.0803 - val_loss: 0.2254 - val_sparse_categorical_crossentropy: 0.1261 - val_sparse_categorical_accuracy: 0.9487 - val_scaled_adversarial_loss: 0.0993\n",
      "Epoch 361/1000\n",
      "11/11 [==============================] - 4s 331ms/step - loss: 0.1850 - sparse_categorical_crossentropy: 0.1039 - sparse_categorical_accuracy: 0.9617 - scaled_adversarial_loss: 0.0811 - val_loss: 0.2248 - val_sparse_categorical_crossentropy: 0.1247 - val_sparse_categorical_accuracy: 0.9517 - val_scaled_adversarial_loss: 0.1001\n",
      "Epoch 362/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.1835 - sparse_categorical_crossentropy: 0.1046 - sparse_categorical_accuracy: 0.9606 - scaled_adversarial_loss: 0.0789 - val_loss: 0.2281 - val_sparse_categorical_crossentropy: 0.1272 - val_sparse_categorical_accuracy: 0.9502 - val_scaled_adversarial_loss: 0.1009\n",
      "Epoch 363/1000\n",
      "11/11 [==============================] - 4s 332ms/step - loss: 0.1807 - sparse_categorical_crossentropy: 0.1025 - sparse_categorical_accuracy: 0.9600 - scaled_adversarial_loss: 0.0782 - val_loss: 0.2374 - val_sparse_categorical_crossentropy: 0.1292 - val_sparse_categorical_accuracy: 0.9487 - val_scaled_adversarial_loss: 0.1082\n",
      "Epoch 364/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.1895 - sparse_categorical_crossentropy: 0.1112 - sparse_categorical_accuracy: 0.9574 - scaled_adversarial_loss: 0.0783 - val_loss: 0.2325 - val_sparse_categorical_crossentropy: 0.1305 - val_sparse_categorical_accuracy: 0.9465 - val_scaled_adversarial_loss: 0.1019\n",
      "Epoch 365/1000\n",
      "11/11 [==============================] - 4s 332ms/step - loss: 0.1894 - sparse_categorical_crossentropy: 0.1075 - sparse_categorical_accuracy: 0.9569 - scaled_adversarial_loss: 0.0819 - val_loss: 0.2191 - val_sparse_categorical_crossentropy: 0.1251 - val_sparse_categorical_accuracy: 0.9494 - val_scaled_adversarial_loss: 0.0940\n",
      "Epoch 366/1000\n",
      "11/11 [==============================] - 4s 332ms/step - loss: 0.1884 - sparse_categorical_crossentropy: 0.1077 - sparse_categorical_accuracy: 0.9611 - scaled_adversarial_loss: 0.0807 - val_loss: 0.2257 - val_sparse_categorical_crossentropy: 0.1264 - val_sparse_categorical_accuracy: 0.9494 - val_scaled_adversarial_loss: 0.0993\n",
      "Epoch 367/1000\n",
      "11/11 [==============================] - 4s 332ms/step - loss: 0.1855 - sparse_categorical_crossentropy: 0.1077 - sparse_categorical_accuracy: 0.9576 - scaled_adversarial_loss: 0.0779 - val_loss: 0.2411 - val_sparse_categorical_crossentropy: 0.1350 - val_sparse_categorical_accuracy: 0.9457 - val_scaled_adversarial_loss: 0.1060\n",
      "Epoch 368/1000\n",
      "11/11 [==============================] - 4s 335ms/step - loss: 0.1891 - sparse_categorical_crossentropy: 0.1091 - sparse_categorical_accuracy: 0.9598 - scaled_adversarial_loss: 0.0800 - val_loss: 0.2209 - val_sparse_categorical_crossentropy: 0.1253 - val_sparse_categorical_accuracy: 0.9465 - val_scaled_adversarial_loss: 0.0955\n",
      "Epoch 369/1000\n",
      "11/11 [==============================] - 4s 331ms/step - loss: 0.1887 - sparse_categorical_crossentropy: 0.1093 - sparse_categorical_accuracy: 0.9589 - scaled_adversarial_loss: 0.0794 - val_loss: 0.2161 - val_sparse_categorical_crossentropy: 0.1287 - val_sparse_categorical_accuracy: 0.9502 - val_scaled_adversarial_loss: 0.0874\n",
      "Epoch 370/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.1839 - sparse_categorical_crossentropy: 0.1042 - sparse_categorical_accuracy: 0.9608 - scaled_adversarial_loss: 0.0797 - val_loss: 0.2214 - val_sparse_categorical_crossentropy: 0.1240 - val_sparse_categorical_accuracy: 0.9494 - val_scaled_adversarial_loss: 0.0974\n",
      "Epoch 371/1000\n",
      "11/11 [==============================] - 4s 335ms/step - loss: 0.1833 - sparse_categorical_crossentropy: 0.1039 - sparse_categorical_accuracy: 0.9591 - scaled_adversarial_loss: 0.0794 - val_loss: 0.2179 - val_sparse_categorical_crossentropy: 0.1260 - val_sparse_categorical_accuracy: 0.9509 - val_scaled_adversarial_loss: 0.0918\n",
      "Epoch 372/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.1892 - sparse_categorical_crossentropy: 0.1086 - sparse_categorical_accuracy: 0.9598 - scaled_adversarial_loss: 0.0806 - val_loss: 0.2359 - val_sparse_categorical_crossentropy: 0.1250 - val_sparse_categorical_accuracy: 0.9502 - val_scaled_adversarial_loss: 0.1110\n",
      "Epoch 373/1000\n",
      "11/11 [==============================] - 4s 339ms/step - loss: 0.1806 - sparse_categorical_crossentropy: 0.1026 - sparse_categorical_accuracy: 0.9610 - scaled_adversarial_loss: 0.0780 - val_loss: 0.2266 - val_sparse_categorical_crossentropy: 0.1240 - val_sparse_categorical_accuracy: 0.9532 - val_scaled_adversarial_loss: 0.1027\n",
      "Epoch 374/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.1810 - sparse_categorical_crossentropy: 0.1049 - sparse_categorical_accuracy: 0.9591 - scaled_adversarial_loss: 0.0762 - val_loss: 0.2300 - val_sparse_categorical_crossentropy: 0.1241 - val_sparse_categorical_accuracy: 0.9517 - val_scaled_adversarial_loss: 0.1059\n",
      "Epoch 375/1000\n",
      "11/11 [==============================] - 4s 332ms/step - loss: 0.1932 - sparse_categorical_crossentropy: 0.1088 - sparse_categorical_accuracy: 0.9585 - scaled_adversarial_loss: 0.0843 - val_loss: 0.2216 - val_sparse_categorical_crossentropy: 0.1252 - val_sparse_categorical_accuracy: 0.9502 - val_scaled_adversarial_loss: 0.0965\n",
      "Epoch 376/1000\n",
      "11/11 [==============================] - 4s 335ms/step - loss: 0.1905 - sparse_categorical_crossentropy: 0.1108 - sparse_categorical_accuracy: 0.9589 - scaled_adversarial_loss: 0.0797 - val_loss: 0.2124 - val_sparse_categorical_crossentropy: 0.1261 - val_sparse_categorical_accuracy: 0.9494 - val_scaled_adversarial_loss: 0.0864\n",
      "Epoch 377/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.1853 - sparse_categorical_crossentropy: 0.1081 - sparse_categorical_accuracy: 0.9637 - scaled_adversarial_loss: 0.0772 - val_loss: 0.2173 - val_sparse_categorical_crossentropy: 0.1220 - val_sparse_categorical_accuracy: 0.9546 - val_scaled_adversarial_loss: 0.0953\n",
      "Epoch 378/1000\n",
      "11/11 [==============================] - 4s 332ms/step - loss: 0.1874 - sparse_categorical_crossentropy: 0.1061 - sparse_categorical_accuracy: 0.9595 - scaled_adversarial_loss: 0.0813 - val_loss: 0.2305 - val_sparse_categorical_crossentropy: 0.1255 - val_sparse_categorical_accuracy: 0.9450 - val_scaled_adversarial_loss: 0.1049\n",
      "Epoch 379/1000\n",
      "11/11 [==============================] - 4s 335ms/step - loss: 0.1869 - sparse_categorical_crossentropy: 0.1090 - sparse_categorical_accuracy: 0.9608 - scaled_adversarial_loss: 0.0779 - val_loss: 0.2214 - val_sparse_categorical_crossentropy: 0.1244 - val_sparse_categorical_accuracy: 0.9487 - val_scaled_adversarial_loss: 0.0970\n",
      "Epoch 380/1000\n",
      "11/11 [==============================] - 4s 337ms/step - loss: 0.1771 - sparse_categorical_crossentropy: 0.1009 - sparse_categorical_accuracy: 0.9621 - scaled_adversarial_loss: 0.0763 - val_loss: 0.2420 - val_sparse_categorical_crossentropy: 0.1273 - val_sparse_categorical_accuracy: 0.9509 - val_scaled_adversarial_loss: 0.1148\n",
      "Epoch 381/1000\n",
      "11/11 [==============================] - 4s 332ms/step - loss: 0.1830 - sparse_categorical_crossentropy: 0.1028 - sparse_categorical_accuracy: 0.9619 - scaled_adversarial_loss: 0.0802 - val_loss: 0.2416 - val_sparse_categorical_crossentropy: 0.1344 - val_sparse_categorical_accuracy: 0.9487 - val_scaled_adversarial_loss: 0.1073\n",
      "Epoch 382/1000\n",
      "11/11 [==============================] - 4s 331ms/step - loss: 0.1773 - sparse_categorical_crossentropy: 0.1013 - sparse_categorical_accuracy: 0.9606 - scaled_adversarial_loss: 0.0760 - val_loss: 0.2295 - val_sparse_categorical_crossentropy: 0.1278 - val_sparse_categorical_accuracy: 0.9494 - val_scaled_adversarial_loss: 0.1018\n",
      "Epoch 383/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.1820 - sparse_categorical_crossentropy: 0.1029 - sparse_categorical_accuracy: 0.9628 - scaled_adversarial_loss: 0.0791 - val_loss: 0.2113 - val_sparse_categorical_crossentropy: 0.1228 - val_sparse_categorical_accuracy: 0.9532 - val_scaled_adversarial_loss: 0.0885\n",
      "Epoch 384/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.1778 - sparse_categorical_crossentropy: 0.1011 - sparse_categorical_accuracy: 0.9637 - scaled_adversarial_loss: 0.0767 - val_loss: 0.2160 - val_sparse_categorical_crossentropy: 0.1190 - val_sparse_categorical_accuracy: 0.9524 - val_scaled_adversarial_loss: 0.0970\n",
      "Epoch 385/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.1755 - sparse_categorical_crossentropy: 0.0982 - sparse_categorical_accuracy: 0.9624 - scaled_adversarial_loss: 0.0773 - val_loss: 0.2175 - val_sparse_categorical_crossentropy: 0.1228 - val_sparse_categorical_accuracy: 0.9524 - val_scaled_adversarial_loss: 0.0946\n",
      "Epoch 386/1000\n",
      "11/11 [==============================] - 4s 336ms/step - loss: 0.1820 - sparse_categorical_crossentropy: 0.1031 - sparse_categorical_accuracy: 0.9602 - scaled_adversarial_loss: 0.0789 - val_loss: 0.2062 - val_sparse_categorical_crossentropy: 0.1169 - val_sparse_categorical_accuracy: 0.9546 - val_scaled_adversarial_loss: 0.0893\n",
      "Epoch 387/1000\n",
      "11/11 [==============================] - 4s 343ms/step - loss: 0.1755 - sparse_categorical_crossentropy: 0.0987 - sparse_categorical_accuracy: 0.9628 - scaled_adversarial_loss: 0.0768 - val_loss: 0.2089 - val_sparse_categorical_crossentropy: 0.1175 - val_sparse_categorical_accuracy: 0.9502 - val_scaled_adversarial_loss: 0.0914\n",
      "Epoch 388/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.1813 - sparse_categorical_crossentropy: 0.1060 - sparse_categorical_accuracy: 0.9611 - scaled_adversarial_loss: 0.0752 - val_loss: 0.2140 - val_sparse_categorical_crossentropy: 0.1217 - val_sparse_categorical_accuracy: 0.9502 - val_scaled_adversarial_loss: 0.0923\n",
      "Epoch 389/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.1843 - sparse_categorical_crossentropy: 0.1048 - sparse_categorical_accuracy: 0.9613 - scaled_adversarial_loss: 0.0795 - val_loss: 0.2092 - val_sparse_categorical_crossentropy: 0.1249 - val_sparse_categorical_accuracy: 0.9532 - val_scaled_adversarial_loss: 0.0843\n",
      "Epoch 390/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.1757 - sparse_categorical_crossentropy: 0.0984 - sparse_categorical_accuracy: 0.9652 - scaled_adversarial_loss: 0.0772 - val_loss: 0.2296 - val_sparse_categorical_crossentropy: 0.1240 - val_sparse_categorical_accuracy: 0.9532 - val_scaled_adversarial_loss: 0.1056\n",
      "Epoch 391/1000\n",
      "11/11 [==============================] - 4s 335ms/step - loss: 0.1824 - sparse_categorical_crossentropy: 0.1036 - sparse_categorical_accuracy: 0.9610 - scaled_adversarial_loss: 0.0788 - val_loss: 0.2101 - val_sparse_categorical_crossentropy: 0.1208 - val_sparse_categorical_accuracy: 0.9524 - val_scaled_adversarial_loss: 0.0893\n",
      "Epoch 392/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.1834 - sparse_categorical_crossentropy: 0.1042 - sparse_categorical_accuracy: 0.9624 - scaled_adversarial_loss: 0.0792 - val_loss: 0.2319 - val_sparse_categorical_crossentropy: 0.1336 - val_sparse_categorical_accuracy: 0.9480 - val_scaled_adversarial_loss: 0.0983\n",
      "Epoch 393/1000\n",
      "11/11 [==============================] - 4s 332ms/step - loss: 0.1818 - sparse_categorical_crossentropy: 0.1032 - sparse_categorical_accuracy: 0.9615 - scaled_adversarial_loss: 0.0785 - val_loss: 0.2362 - val_sparse_categorical_crossentropy: 0.1280 - val_sparse_categorical_accuracy: 0.9494 - val_scaled_adversarial_loss: 0.1082\n",
      "Epoch 394/1000\n",
      "11/11 [==============================] - 4s 332ms/step - loss: 0.1811 - sparse_categorical_crossentropy: 0.1020 - sparse_categorical_accuracy: 0.9624 - scaled_adversarial_loss: 0.0790 - val_loss: 0.2466 - val_sparse_categorical_crossentropy: 0.1256 - val_sparse_categorical_accuracy: 0.9450 - val_scaled_adversarial_loss: 0.1211\n",
      "Epoch 395/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.1915 - sparse_categorical_crossentropy: 0.1097 - sparse_categorical_accuracy: 0.9604 - scaled_adversarial_loss: 0.0818 - val_loss: 0.2208 - val_sparse_categorical_crossentropy: 0.1271 - val_sparse_categorical_accuracy: 0.9487 - val_scaled_adversarial_loss: 0.0937\n",
      "Epoch 396/1000\n",
      "11/11 [==============================] - 4s 332ms/step - loss: 0.1832 - sparse_categorical_crossentropy: 0.1027 - sparse_categorical_accuracy: 0.9639 - scaled_adversarial_loss: 0.0804 - val_loss: 0.2139 - val_sparse_categorical_crossentropy: 0.1223 - val_sparse_categorical_accuracy: 0.9509 - val_scaled_adversarial_loss: 0.0916\n",
      "Epoch 397/1000\n",
      "11/11 [==============================] - 4s 332ms/step - loss: 0.1820 - sparse_categorical_crossentropy: 0.1041 - sparse_categorical_accuracy: 0.9649 - scaled_adversarial_loss: 0.0778 - val_loss: 0.2013 - val_sparse_categorical_crossentropy: 0.1204 - val_sparse_categorical_accuracy: 0.9532 - val_scaled_adversarial_loss: 0.0809\n",
      "Epoch 398/1000\n",
      "11/11 [==============================] - 4s 332ms/step - loss: 0.1718 - sparse_categorical_crossentropy: 0.0952 - sparse_categorical_accuracy: 0.9637 - scaled_adversarial_loss: 0.0767 - val_loss: 0.2090 - val_sparse_categorical_crossentropy: 0.1228 - val_sparse_categorical_accuracy: 0.9524 - val_scaled_adversarial_loss: 0.0861\n",
      "Epoch 399/1000\n",
      "11/11 [==============================] - 4s 330ms/step - loss: 0.1774 - sparse_categorical_crossentropy: 0.1013 - sparse_categorical_accuracy: 0.9619 - scaled_adversarial_loss: 0.0762 - val_loss: 0.2034 - val_sparse_categorical_crossentropy: 0.1239 - val_sparse_categorical_accuracy: 0.9524 - val_scaled_adversarial_loss: 0.0795\n",
      "Epoch 400/1000\n",
      "11/11 [==============================] - 4s 335ms/step - loss: 0.1807 - sparse_categorical_crossentropy: 0.1050 - sparse_categorical_accuracy: 0.9632 - scaled_adversarial_loss: 0.0757 - val_loss: 0.2027 - val_sparse_categorical_crossentropy: 0.1185 - val_sparse_categorical_accuracy: 0.9524 - val_scaled_adversarial_loss: 0.0842\n",
      "Epoch 401/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.1679 - sparse_categorical_crossentropy: 0.0940 - sparse_categorical_accuracy: 0.9663 - scaled_adversarial_loss: 0.0739 - val_loss: 0.2145 - val_sparse_categorical_crossentropy: 0.1207 - val_sparse_categorical_accuracy: 0.9554 - val_scaled_adversarial_loss: 0.0938\n",
      "Epoch 402/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.1727 - sparse_categorical_crossentropy: 0.0937 - sparse_categorical_accuracy: 0.9645 - scaled_adversarial_loss: 0.0790 - val_loss: 0.2159 - val_sparse_categorical_crossentropy: 0.1245 - val_sparse_categorical_accuracy: 0.9509 - val_scaled_adversarial_loss: 0.0914\n",
      "Epoch 403/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.1777 - sparse_categorical_crossentropy: 0.1037 - sparse_categorical_accuracy: 0.9615 - scaled_adversarial_loss: 0.0740 - val_loss: 0.2071 - val_sparse_categorical_crossentropy: 0.1192 - val_sparse_categorical_accuracy: 0.9509 - val_scaled_adversarial_loss: 0.0879\n",
      "Epoch 404/1000\n",
      "11/11 [==============================] - 4s 332ms/step - loss: 0.1760 - sparse_categorical_crossentropy: 0.0983 - sparse_categorical_accuracy: 0.9623 - scaled_adversarial_loss: 0.0776 - val_loss: 0.2179 - val_sparse_categorical_crossentropy: 0.1217 - val_sparse_categorical_accuracy: 0.9524 - val_scaled_adversarial_loss: 0.0962\n",
      "Epoch 405/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.1705 - sparse_categorical_crossentropy: 0.0977 - sparse_categorical_accuracy: 0.9639 - scaled_adversarial_loss: 0.0728 - val_loss: 0.2180 - val_sparse_categorical_crossentropy: 0.1236 - val_sparse_categorical_accuracy: 0.9517 - val_scaled_adversarial_loss: 0.0944\n",
      "Epoch 406/1000\n",
      "11/11 [==============================] - 4s 341ms/step - loss: 0.1745 - sparse_categorical_crossentropy: 0.0976 - sparse_categorical_accuracy: 0.9654 - scaled_adversarial_loss: 0.0769 - val_loss: 0.2296 - val_sparse_categorical_crossentropy: 0.1291 - val_sparse_categorical_accuracy: 0.9532 - val_scaled_adversarial_loss: 0.1005\n",
      "Epoch 407/1000\n",
      "11/11 [==============================] - 4s 330ms/step - loss: 0.1770 - sparse_categorical_crossentropy: 0.0993 - sparse_categorical_accuracy: 0.9626 - scaled_adversarial_loss: 0.0777 - val_loss: 0.2081 - val_sparse_categorical_crossentropy: 0.1211 - val_sparse_categorical_accuracy: 0.9494 - val_scaled_adversarial_loss: 0.0870\n",
      "Epoch 408/1000\n",
      "11/11 [==============================] - 4s 328ms/step - loss: 0.1714 - sparse_categorical_crossentropy: 0.0970 - sparse_categorical_accuracy: 0.9649 - scaled_adversarial_loss: 0.0745 - val_loss: 0.2093 - val_sparse_categorical_crossentropy: 0.1218 - val_sparse_categorical_accuracy: 0.9539 - val_scaled_adversarial_loss: 0.0874\n",
      "Epoch 409/1000\n",
      "11/11 [==============================] - 4s 323ms/step - loss: 0.1759 - sparse_categorical_crossentropy: 0.0998 - sparse_categorical_accuracy: 0.9632 - scaled_adversarial_loss: 0.0761 - val_loss: 0.2209 - val_sparse_categorical_crossentropy: 0.1201 - val_sparse_categorical_accuracy: 0.9561 - val_scaled_adversarial_loss: 0.1008\n",
      "Epoch 410/1000\n",
      "11/11 [==============================] - 4s 327ms/step - loss: 0.1730 - sparse_categorical_crossentropy: 0.0960 - sparse_categorical_accuracy: 0.9673 - scaled_adversarial_loss: 0.0770 - val_loss: 0.2366 - val_sparse_categorical_crossentropy: 0.1281 - val_sparse_categorical_accuracy: 0.9494 - val_scaled_adversarial_loss: 0.1084\n",
      "Epoch 411/1000\n",
      "11/11 [==============================] - 4s 332ms/step - loss: 0.1775 - sparse_categorical_crossentropy: 0.0999 - sparse_categorical_accuracy: 0.9624 - scaled_adversarial_loss: 0.0776 - val_loss: 0.2256 - val_sparse_categorical_crossentropy: 0.1220 - val_sparse_categorical_accuracy: 0.9576 - val_scaled_adversarial_loss: 0.1036\n",
      "Epoch 412/1000\n",
      "11/11 [==============================] - 4s 330ms/step - loss: 0.1749 - sparse_categorical_crossentropy: 0.0976 - sparse_categorical_accuracy: 0.9636 - scaled_adversarial_loss: 0.0773 - val_loss: 0.2167 - val_sparse_categorical_crossentropy: 0.1268 - val_sparse_categorical_accuracy: 0.9539 - val_scaled_adversarial_loss: 0.0899\n",
      "Epoch 413/1000\n",
      "11/11 [==============================] - 4s 328ms/step - loss: 0.1670 - sparse_categorical_crossentropy: 0.0920 - sparse_categorical_accuracy: 0.9649 - scaled_adversarial_loss: 0.0750 - val_loss: 0.2194 - val_sparse_categorical_crossentropy: 0.1254 - val_sparse_categorical_accuracy: 0.9546 - val_scaled_adversarial_loss: 0.0940\n",
      "Epoch 414/1000\n",
      "11/11 [==============================] - 4s 324ms/step - loss: 0.1720 - sparse_categorical_crossentropy: 0.0947 - sparse_categorical_accuracy: 0.9654 - scaled_adversarial_loss: 0.0773 - val_loss: 0.2309 - val_sparse_categorical_crossentropy: 0.1303 - val_sparse_categorical_accuracy: 0.9509 - val_scaled_adversarial_loss: 0.1006\n",
      "Epoch 415/1000\n",
      "11/11 [==============================] - 4s 327ms/step - loss: 0.1705 - sparse_categorical_crossentropy: 0.0956 - sparse_categorical_accuracy: 0.9636 - scaled_adversarial_loss: 0.0749 - val_loss: 0.2451 - val_sparse_categorical_crossentropy: 0.1433 - val_sparse_categorical_accuracy: 0.9465 - val_scaled_adversarial_loss: 0.1017\n",
      "Epoch 416/1000\n",
      "11/11 [==============================] - 4s 325ms/step - loss: 0.1766 - sparse_categorical_crossentropy: 0.1017 - sparse_categorical_accuracy: 0.9608 - scaled_adversarial_loss: 0.0748 - val_loss: 0.2114 - val_sparse_categorical_crossentropy: 0.1242 - val_sparse_categorical_accuracy: 0.9532 - val_scaled_adversarial_loss: 0.0872\n",
      "Epoch 417/1000\n",
      "11/11 [==============================] - 4s 328ms/step - loss: 0.1773 - sparse_categorical_crossentropy: 0.0979 - sparse_categorical_accuracy: 0.9636 - scaled_adversarial_loss: 0.0794 - val_loss: 0.2229 - val_sparse_categorical_crossentropy: 0.1232 - val_sparse_categorical_accuracy: 0.9524 - val_scaled_adversarial_loss: 0.0996\n",
      "Epoch 418/1000\n",
      "11/11 [==============================] - 4s 330ms/step - loss: 0.1775 - sparse_categorical_crossentropy: 0.1030 - sparse_categorical_accuracy: 0.9636 - scaled_adversarial_loss: 0.0745 - val_loss: 0.2203 - val_sparse_categorical_crossentropy: 0.1164 - val_sparse_categorical_accuracy: 0.9509 - val_scaled_adversarial_loss: 0.1039\n",
      "Epoch 419/1000\n",
      "11/11 [==============================] - 4s 330ms/step - loss: 0.1727 - sparse_categorical_crossentropy: 0.0956 - sparse_categorical_accuracy: 0.9656 - scaled_adversarial_loss: 0.0771 - val_loss: 0.2261 - val_sparse_categorical_crossentropy: 0.1271 - val_sparse_categorical_accuracy: 0.9517 - val_scaled_adversarial_loss: 0.0990\n",
      "Epoch 420/1000\n",
      "11/11 [==============================] - 4s 327ms/step - loss: 0.1730 - sparse_categorical_crossentropy: 0.0975 - sparse_categorical_accuracy: 0.9641 - scaled_adversarial_loss: 0.0755 - val_loss: 0.2092 - val_sparse_categorical_crossentropy: 0.1179 - val_sparse_categorical_accuracy: 0.9546 - val_scaled_adversarial_loss: 0.0913\n",
      "Epoch 421/1000\n",
      "11/11 [==============================] - 4s 325ms/step - loss: 0.1673 - sparse_categorical_crossentropy: 0.0923 - sparse_categorical_accuracy: 0.9667 - scaled_adversarial_loss: 0.0750 - val_loss: 0.2162 - val_sparse_categorical_crossentropy: 0.1258 - val_sparse_categorical_accuracy: 0.9502 - val_scaled_adversarial_loss: 0.0905\n",
      "Epoch 422/1000\n",
      "11/11 [==============================] - 4s 325ms/step - loss: 0.1734 - sparse_categorical_crossentropy: 0.0964 - sparse_categorical_accuracy: 0.9665 - scaled_adversarial_loss: 0.0770 - val_loss: 0.2239 - val_sparse_categorical_crossentropy: 0.1222 - val_sparse_categorical_accuracy: 0.9502 - val_scaled_adversarial_loss: 0.1017\n",
      "Epoch 423/1000\n",
      "11/11 [==============================] - 4s 327ms/step - loss: 0.1739 - sparse_categorical_crossentropy: 0.1025 - sparse_categorical_accuracy: 0.9628 - scaled_adversarial_loss: 0.0714 - val_loss: 0.2189 - val_sparse_categorical_crossentropy: 0.1263 - val_sparse_categorical_accuracy: 0.9532 - val_scaled_adversarial_loss: 0.0927\n",
      "Epoch 424/1000\n",
      "11/11 [==============================] - 4s 330ms/step - loss: 0.1680 - sparse_categorical_crossentropy: 0.0909 - sparse_categorical_accuracy: 0.9673 - scaled_adversarial_loss: 0.0771 - val_loss: 0.2292 - val_sparse_categorical_crossentropy: 0.1289 - val_sparse_categorical_accuracy: 0.9517 - val_scaled_adversarial_loss: 0.1002\n",
      "Epoch 425/1000\n",
      "11/11 [==============================] - 4s 327ms/step - loss: 0.1737 - sparse_categorical_crossentropy: 0.0968 - sparse_categorical_accuracy: 0.9652 - scaled_adversarial_loss: 0.0769 - val_loss: 0.2305 - val_sparse_categorical_crossentropy: 0.1289 - val_sparse_categorical_accuracy: 0.9509 - val_scaled_adversarial_loss: 0.1016\n",
      "Epoch 426/1000\n",
      "11/11 [==============================] - 4s 327ms/step - loss: 0.1705 - sparse_categorical_crossentropy: 0.0961 - sparse_categorical_accuracy: 0.9660 - scaled_adversarial_loss: 0.0744 - val_loss: 0.2021 - val_sparse_categorical_crossentropy: 0.1183 - val_sparse_categorical_accuracy: 0.9539 - val_scaled_adversarial_loss: 0.0839\n",
      "Epoch 427/1000\n",
      "11/11 [==============================] - 4s 330ms/step - loss: 0.1723 - sparse_categorical_crossentropy: 0.0965 - sparse_categorical_accuracy: 0.9643 - scaled_adversarial_loss: 0.0758 - val_loss: 0.2185 - val_sparse_categorical_crossentropy: 0.1257 - val_sparse_categorical_accuracy: 0.9524 - val_scaled_adversarial_loss: 0.0928\n",
      "Epoch 428/1000\n",
      "11/11 [==============================] - 4s 328ms/step - loss: 0.1719 - sparse_categorical_crossentropy: 0.0935 - sparse_categorical_accuracy: 0.9665 - scaled_adversarial_loss: 0.0784 - val_loss: 0.2098 - val_sparse_categorical_crossentropy: 0.1183 - val_sparse_categorical_accuracy: 0.9524 - val_scaled_adversarial_loss: 0.0915\n",
      "Epoch 429/1000\n",
      "11/11 [==============================] - 4s 327ms/step - loss: 0.1726 - sparse_categorical_crossentropy: 0.0962 - sparse_categorical_accuracy: 0.9663 - scaled_adversarial_loss: 0.0765 - val_loss: 0.2156 - val_sparse_categorical_crossentropy: 0.1237 - val_sparse_categorical_accuracy: 0.9561 - val_scaled_adversarial_loss: 0.0919\n",
      "Epoch 430/1000\n",
      "11/11 [==============================] - 4s 326ms/step - loss: 0.1670 - sparse_categorical_crossentropy: 0.0940 - sparse_categorical_accuracy: 0.9656 - scaled_adversarial_loss: 0.0731 - val_loss: 0.2171 - val_sparse_categorical_crossentropy: 0.1268 - val_sparse_categorical_accuracy: 0.9554 - val_scaled_adversarial_loss: 0.0904\n",
      "Epoch 431/1000\n",
      "11/11 [==============================] - 4s 331ms/step - loss: 0.1769 - sparse_categorical_crossentropy: 0.1012 - sparse_categorical_accuracy: 0.9623 - scaled_adversarial_loss: 0.0757 - val_loss: 0.2082 - val_sparse_categorical_crossentropy: 0.1213 - val_sparse_categorical_accuracy: 0.9546 - val_scaled_adversarial_loss: 0.0869\n",
      "Epoch 432/1000\n",
      "11/11 [==============================] - 4s 328ms/step - loss: 0.1699 - sparse_categorical_crossentropy: 0.0964 - sparse_categorical_accuracy: 0.9645 - scaled_adversarial_loss: 0.0734 - val_loss: 0.2006 - val_sparse_categorical_crossentropy: 0.1157 - val_sparse_categorical_accuracy: 0.9546 - val_scaled_adversarial_loss: 0.0849\n",
      "Epoch 433/1000\n",
      "11/11 [==============================] - 4s 331ms/step - loss: 0.1688 - sparse_categorical_crossentropy: 0.0953 - sparse_categorical_accuracy: 0.9652 - scaled_adversarial_loss: 0.0736 - val_loss: 0.2006 - val_sparse_categorical_crossentropy: 0.1215 - val_sparse_categorical_accuracy: 0.9532 - val_scaled_adversarial_loss: 0.0791\n",
      "Epoch 434/1000\n",
      "11/11 [==============================] - 4s 326ms/step - loss: 0.1679 - sparse_categorical_crossentropy: 0.0921 - sparse_categorical_accuracy: 0.9688 - scaled_adversarial_loss: 0.0758 - val_loss: 0.2095 - val_sparse_categorical_crossentropy: 0.1165 - val_sparse_categorical_accuracy: 0.9584 - val_scaled_adversarial_loss: 0.0931\n",
      "Epoch 435/1000\n",
      "11/11 [==============================] - 4s 332ms/step - loss: 0.1736 - sparse_categorical_crossentropy: 0.0974 - sparse_categorical_accuracy: 0.9647 - scaled_adversarial_loss: 0.0762 - val_loss: 0.2014 - val_sparse_categorical_crossentropy: 0.1189 - val_sparse_categorical_accuracy: 0.9517 - val_scaled_adversarial_loss: 0.0825\n",
      "Epoch 436/1000\n",
      "11/11 [==============================] - 4s 330ms/step - loss: 0.1738 - sparse_categorical_crossentropy: 0.0989 - sparse_categorical_accuracy: 0.9624 - scaled_adversarial_loss: 0.0749 - val_loss: 0.1999 - val_sparse_categorical_crossentropy: 0.1218 - val_sparse_categorical_accuracy: 0.9480 - val_scaled_adversarial_loss: 0.0781\n",
      "Epoch 437/1000\n",
      "11/11 [==============================] - 4s 330ms/step - loss: 0.1743 - sparse_categorical_crossentropy: 0.0977 - sparse_categorical_accuracy: 0.9643 - scaled_adversarial_loss: 0.0766 - val_loss: 0.2137 - val_sparse_categorical_crossentropy: 0.1220 - val_sparse_categorical_accuracy: 0.9524 - val_scaled_adversarial_loss: 0.0917\n",
      "Epoch 438/1000\n",
      "11/11 [==============================] - 4s 329ms/step - loss: 0.1690 - sparse_categorical_crossentropy: 0.0953 - sparse_categorical_accuracy: 0.9662 - scaled_adversarial_loss: 0.0737 - val_loss: 0.2238 - val_sparse_categorical_crossentropy: 0.1280 - val_sparse_categorical_accuracy: 0.9472 - val_scaled_adversarial_loss: 0.0958\n",
      "Epoch 439/1000\n",
      "11/11 [==============================] - 4s 332ms/step - loss: 0.1654 - sparse_categorical_crossentropy: 0.0934 - sparse_categorical_accuracy: 0.9669 - scaled_adversarial_loss: 0.0720 - val_loss: 0.2040 - val_sparse_categorical_crossentropy: 0.1152 - val_sparse_categorical_accuracy: 0.9539 - val_scaled_adversarial_loss: 0.0888\n",
      "Epoch 440/1000\n",
      "11/11 [==============================] - 4s 325ms/step - loss: 0.1714 - sparse_categorical_crossentropy: 0.0957 - sparse_categorical_accuracy: 0.9656 - scaled_adversarial_loss: 0.0757 - val_loss: 0.2055 - val_sparse_categorical_crossentropy: 0.1218 - val_sparse_categorical_accuracy: 0.9502 - val_scaled_adversarial_loss: 0.0837\n",
      "Epoch 441/1000\n",
      "11/11 [==============================] - 4s 329ms/step - loss: 0.1660 - sparse_categorical_crossentropy: 0.0908 - sparse_categorical_accuracy: 0.9689 - scaled_adversarial_loss: 0.0752 - val_loss: 0.2166 - val_sparse_categorical_crossentropy: 0.1169 - val_sparse_categorical_accuracy: 0.9561 - val_scaled_adversarial_loss: 0.0998\n",
      "Epoch 442/1000\n",
      "11/11 [==============================] - 4s 332ms/step - loss: 0.1621 - sparse_categorical_crossentropy: 0.0888 - sparse_categorical_accuracy: 0.9699 - scaled_adversarial_loss: 0.0733 - val_loss: 0.2294 - val_sparse_categorical_crossentropy: 0.1238 - val_sparse_categorical_accuracy: 0.9502 - val_scaled_adversarial_loss: 0.1057\n",
      "Epoch 443/1000\n",
      "11/11 [==============================] - 4s 329ms/step - loss: 0.1664 - sparse_categorical_crossentropy: 0.0911 - sparse_categorical_accuracy: 0.9649 - scaled_adversarial_loss: 0.0753 - val_loss: 0.2435 - val_sparse_categorical_crossentropy: 0.1365 - val_sparse_categorical_accuracy: 0.9509 - val_scaled_adversarial_loss: 0.1070\n",
      "Epoch 444/1000\n",
      "11/11 [==============================] - 4s 330ms/step - loss: 0.1724 - sparse_categorical_crossentropy: 0.0969 - sparse_categorical_accuracy: 0.9637 - scaled_adversarial_loss: 0.0756 - val_loss: 0.2335 - val_sparse_categorical_crossentropy: 0.1297 - val_sparse_categorical_accuracy: 0.9517 - val_scaled_adversarial_loss: 0.1038\n",
      "Epoch 445/1000\n",
      "11/11 [==============================] - 4s 329ms/step - loss: 0.1645 - sparse_categorical_crossentropy: 0.0908 - sparse_categorical_accuracy: 0.9658 - scaled_adversarial_loss: 0.0737 - val_loss: 0.2107 - val_sparse_categorical_crossentropy: 0.1156 - val_sparse_categorical_accuracy: 0.9554 - val_scaled_adversarial_loss: 0.0951\n",
      "Epoch 446/1000\n",
      "11/11 [==============================] - 4s 328ms/step - loss: 0.1617 - sparse_categorical_crossentropy: 0.0884 - sparse_categorical_accuracy: 0.9662 - scaled_adversarial_loss: 0.0734 - val_loss: 0.2110 - val_sparse_categorical_crossentropy: 0.1210 - val_sparse_categorical_accuracy: 0.9532 - val_scaled_adversarial_loss: 0.0900\n",
      "Epoch 447/1000\n",
      "11/11 [==============================] - 4s 330ms/step - loss: 0.1641 - sparse_categorical_crossentropy: 0.0885 - sparse_categorical_accuracy: 0.9682 - scaled_adversarial_loss: 0.0757 - val_loss: 0.2090 - val_sparse_categorical_crossentropy: 0.1264 - val_sparse_categorical_accuracy: 0.9524 - val_scaled_adversarial_loss: 0.0826\n",
      "Epoch 448/1000\n",
      "11/11 [==============================] - 4s 328ms/step - loss: 0.1688 - sparse_categorical_crossentropy: 0.0942 - sparse_categorical_accuracy: 0.9667 - scaled_adversarial_loss: 0.0746 - val_loss: 0.2037 - val_sparse_categorical_crossentropy: 0.1204 - val_sparse_categorical_accuracy: 0.9554 - val_scaled_adversarial_loss: 0.0833\n",
      "Epoch 449/1000\n",
      "11/11 [==============================] - 4s 329ms/step - loss: 0.1594 - sparse_categorical_crossentropy: 0.0899 - sparse_categorical_accuracy: 0.9675 - scaled_adversarial_loss: 0.0696 - val_loss: 0.2048 - val_sparse_categorical_crossentropy: 0.1192 - val_sparse_categorical_accuracy: 0.9561 - val_scaled_adversarial_loss: 0.0856\n",
      "Epoch 450/1000\n",
      "11/11 [==============================] - 4s 330ms/step - loss: 0.1709 - sparse_categorical_crossentropy: 0.0967 - sparse_categorical_accuracy: 0.9650 - scaled_adversarial_loss: 0.0742 - val_loss: 0.2182 - val_sparse_categorical_crossentropy: 0.1241 - val_sparse_categorical_accuracy: 0.9554 - val_scaled_adversarial_loss: 0.0941\n",
      "Epoch 451/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.1666 - sparse_categorical_crossentropy: 0.0923 - sparse_categorical_accuracy: 0.9684 - scaled_adversarial_loss: 0.0743 - val_loss: 0.1972 - val_sparse_categorical_crossentropy: 0.1167 - val_sparse_categorical_accuracy: 0.9554 - val_scaled_adversarial_loss: 0.0805\n",
      "Epoch 452/1000\n",
      "11/11 [==============================] - 4s 329ms/step - loss: 0.1654 - sparse_categorical_crossentropy: 0.0933 - sparse_categorical_accuracy: 0.9663 - scaled_adversarial_loss: 0.0721 - val_loss: 0.2066 - val_sparse_categorical_crossentropy: 0.1162 - val_sparse_categorical_accuracy: 0.9576 - val_scaled_adversarial_loss: 0.0904\n",
      "Epoch 453/1000\n",
      "11/11 [==============================] - 4s 327ms/step - loss: 0.1665 - sparse_categorical_crossentropy: 0.0926 - sparse_categorical_accuracy: 0.9656 - scaled_adversarial_loss: 0.0739 - val_loss: 0.2101 - val_sparse_categorical_crossentropy: 0.1163 - val_sparse_categorical_accuracy: 0.9487 - val_scaled_adversarial_loss: 0.0938\n",
      "Epoch 454/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.1633 - sparse_categorical_crossentropy: 0.0909 - sparse_categorical_accuracy: 0.9660 - scaled_adversarial_loss: 0.0724 - val_loss: 0.2351 - val_sparse_categorical_crossentropy: 0.1259 - val_sparse_categorical_accuracy: 0.9502 - val_scaled_adversarial_loss: 0.1093\n",
      "Epoch 455/1000\n",
      "11/11 [==============================] - 4s 331ms/step - loss: 0.1665 - sparse_categorical_crossentropy: 0.0891 - sparse_categorical_accuracy: 0.9675 - scaled_adversarial_loss: 0.0773 - val_loss: 0.2269 - val_sparse_categorical_crossentropy: 0.1236 - val_sparse_categorical_accuracy: 0.9494 - val_scaled_adversarial_loss: 0.1033\n",
      "Epoch 456/1000\n",
      "11/11 [==============================] - 4s 332ms/step - loss: 0.1714 - sparse_categorical_crossentropy: 0.0955 - sparse_categorical_accuracy: 0.9637 - scaled_adversarial_loss: 0.0760 - val_loss: 0.2159 - val_sparse_categorical_crossentropy: 0.1181 - val_sparse_categorical_accuracy: 0.9524 - val_scaled_adversarial_loss: 0.0977\n",
      "Epoch 457/1000\n",
      "11/11 [==============================] - 4s 331ms/step - loss: 0.1666 - sparse_categorical_crossentropy: 0.0921 - sparse_categorical_accuracy: 0.9658 - scaled_adversarial_loss: 0.0745 - val_loss: 0.2214 - val_sparse_categorical_crossentropy: 0.1199 - val_sparse_categorical_accuracy: 0.9546 - val_scaled_adversarial_loss: 0.1016\n",
      "Epoch 458/1000\n",
      "11/11 [==============================] - 4s 339ms/step - loss: 0.1683 - sparse_categorical_crossentropy: 0.0916 - sparse_categorical_accuracy: 0.9658 - scaled_adversarial_loss: 0.0767 - val_loss: 0.2414 - val_sparse_categorical_crossentropy: 0.1368 - val_sparse_categorical_accuracy: 0.9532 - val_scaled_adversarial_loss: 0.1046\n",
      "Epoch 459/1000\n",
      "11/11 [==============================] - 4s 329ms/step - loss: 0.1696 - sparse_categorical_crossentropy: 0.0939 - sparse_categorical_accuracy: 0.9663 - scaled_adversarial_loss: 0.0757 - val_loss: 0.2254 - val_sparse_categorical_crossentropy: 0.1261 - val_sparse_categorical_accuracy: 0.9509 - val_scaled_adversarial_loss: 0.0993\n",
      "Epoch 460/1000\n",
      "11/11 [==============================] - 4s 331ms/step - loss: 0.1646 - sparse_categorical_crossentropy: 0.0924 - sparse_categorical_accuracy: 0.9650 - scaled_adversarial_loss: 0.0722 - val_loss: 0.2283 - val_sparse_categorical_crossentropy: 0.1230 - val_sparse_categorical_accuracy: 0.9509 - val_scaled_adversarial_loss: 0.1053\n",
      "Epoch 461/1000\n",
      "11/11 [==============================] - 4s 332ms/step - loss: 0.1713 - sparse_categorical_crossentropy: 0.0969 - sparse_categorical_accuracy: 0.9630 - scaled_adversarial_loss: 0.0744 - val_loss: 0.2249 - val_sparse_categorical_crossentropy: 0.1227 - val_sparse_categorical_accuracy: 0.9561 - val_scaled_adversarial_loss: 0.1022\n",
      "Epoch 462/1000\n",
      "11/11 [==============================] - 4s 331ms/step - loss: 0.1715 - sparse_categorical_crossentropy: 0.0940 - sparse_categorical_accuracy: 0.9671 - scaled_adversarial_loss: 0.0775 - val_loss: 0.1991 - val_sparse_categorical_crossentropy: 0.1181 - val_sparse_categorical_accuracy: 0.9569 - val_scaled_adversarial_loss: 0.0810\n",
      "Epoch 463/1000\n",
      "11/11 [==============================] - 4s 325ms/step - loss: 0.1629 - sparse_categorical_crossentropy: 0.0916 - sparse_categorical_accuracy: 0.9676 - scaled_adversarial_loss: 0.0713 - val_loss: 0.2067 - val_sparse_categorical_crossentropy: 0.1160 - val_sparse_categorical_accuracy: 0.9539 - val_scaled_adversarial_loss: 0.0907\n",
      "Epoch 464/1000\n",
      "11/11 [==============================] - 4s 325ms/step - loss: 0.1564 - sparse_categorical_crossentropy: 0.0831 - sparse_categorical_accuracy: 0.9716 - scaled_adversarial_loss: 0.0734 - val_loss: 0.2109 - val_sparse_categorical_crossentropy: 0.1183 - val_sparse_categorical_accuracy: 0.9554 - val_scaled_adversarial_loss: 0.0926\n",
      "Epoch 465/1000\n",
      "11/11 [==============================] - 4s 324ms/step - loss: 0.1665 - sparse_categorical_crossentropy: 0.0931 - sparse_categorical_accuracy: 0.9656 - scaled_adversarial_loss: 0.0734 - val_loss: 0.2039 - val_sparse_categorical_crossentropy: 0.1180 - val_sparse_categorical_accuracy: 0.9554 - val_scaled_adversarial_loss: 0.0859\n",
      "Epoch 466/1000\n",
      "11/11 [==============================] - 4s 326ms/step - loss: 0.1653 - sparse_categorical_crossentropy: 0.0932 - sparse_categorical_accuracy: 0.9665 - scaled_adversarial_loss: 0.0721 - val_loss: 0.2228 - val_sparse_categorical_crossentropy: 0.1258 - val_sparse_categorical_accuracy: 0.9546 - val_scaled_adversarial_loss: 0.0970\n",
      "Epoch 467/1000\n",
      "11/11 [==============================] - 4s 324ms/step - loss: 0.1686 - sparse_categorical_crossentropy: 0.0915 - sparse_categorical_accuracy: 0.9676 - scaled_adversarial_loss: 0.0771 - val_loss: 0.2045 - val_sparse_categorical_crossentropy: 0.1167 - val_sparse_categorical_accuracy: 0.9554 - val_scaled_adversarial_loss: 0.0878\n",
      "Epoch 468/1000\n",
      "11/11 [==============================] - 4s 325ms/step - loss: 0.1584 - sparse_categorical_crossentropy: 0.0889 - sparse_categorical_accuracy: 0.9689 - scaled_adversarial_loss: 0.0695 - val_loss: 0.2054 - val_sparse_categorical_crossentropy: 0.1222 - val_sparse_categorical_accuracy: 0.9524 - val_scaled_adversarial_loss: 0.0832\n",
      "Epoch 469/1000\n",
      "11/11 [==============================] - 4s 323ms/step - loss: 0.1609 - sparse_categorical_crossentropy: 0.0882 - sparse_categorical_accuracy: 0.9680 - scaled_adversarial_loss: 0.0727 - val_loss: 0.1934 - val_sparse_categorical_crossentropy: 0.1137 - val_sparse_categorical_accuracy: 0.9561 - val_scaled_adversarial_loss: 0.0797\n",
      "Epoch 470/1000\n",
      "11/11 [==============================] - 4s 327ms/step - loss: 0.1653 - sparse_categorical_crossentropy: 0.0912 - sparse_categorical_accuracy: 0.9676 - scaled_adversarial_loss: 0.0741 - val_loss: 0.1973 - val_sparse_categorical_crossentropy: 0.1122 - val_sparse_categorical_accuracy: 0.9546 - val_scaled_adversarial_loss: 0.0851\n",
      "Epoch 471/1000\n",
      "11/11 [==============================] - 4s 329ms/step - loss: 0.1636 - sparse_categorical_crossentropy: 0.0904 - sparse_categorical_accuracy: 0.9688 - scaled_adversarial_loss: 0.0732 - val_loss: 0.2235 - val_sparse_categorical_crossentropy: 0.1253 - val_sparse_categorical_accuracy: 0.9584 - val_scaled_adversarial_loss: 0.0982\n",
      "Epoch 472/1000\n",
      "11/11 [==============================] - 4s 332ms/step - loss: 0.1641 - sparse_categorical_crossentropy: 0.0917 - sparse_categorical_accuracy: 0.9634 - scaled_adversarial_loss: 0.0724 - val_loss: 0.2012 - val_sparse_categorical_crossentropy: 0.1168 - val_sparse_categorical_accuracy: 0.9509 - val_scaled_adversarial_loss: 0.0844\n",
      "Epoch 473/1000\n",
      "11/11 [==============================] - 4s 332ms/step - loss: 0.1649 - sparse_categorical_crossentropy: 0.0919 - sparse_categorical_accuracy: 0.9673 - scaled_adversarial_loss: 0.0731 - val_loss: 0.1921 - val_sparse_categorical_crossentropy: 0.1111 - val_sparse_categorical_accuracy: 0.9517 - val_scaled_adversarial_loss: 0.0810\n",
      "Epoch 474/1000\n",
      "11/11 [==============================] - 4s 332ms/step - loss: 0.1589 - sparse_categorical_crossentropy: 0.0862 - sparse_categorical_accuracy: 0.9708 - scaled_adversarial_loss: 0.0726 - val_loss: 0.2046 - val_sparse_categorical_crossentropy: 0.1118 - val_sparse_categorical_accuracy: 0.9576 - val_scaled_adversarial_loss: 0.0928\n",
      "Epoch 475/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.1576 - sparse_categorical_crossentropy: 0.0868 - sparse_categorical_accuracy: 0.9708 - scaled_adversarial_loss: 0.0707 - val_loss: 0.2106 - val_sparse_categorical_crossentropy: 0.1151 - val_sparse_categorical_accuracy: 0.9532 - val_scaled_adversarial_loss: 0.0955\n",
      "Epoch 476/1000\n",
      "11/11 [==============================] - 4s 329ms/step - loss: 0.1601 - sparse_categorical_crossentropy: 0.0879 - sparse_categorical_accuracy: 0.9691 - scaled_adversarial_loss: 0.0722 - val_loss: 0.2131 - val_sparse_categorical_crossentropy: 0.1248 - val_sparse_categorical_accuracy: 0.9494 - val_scaled_adversarial_loss: 0.0883\n",
      "Epoch 477/1000\n",
      "11/11 [==============================] - 4s 327ms/step - loss: 0.1631 - sparse_categorical_crossentropy: 0.0925 - sparse_categorical_accuracy: 0.9658 - scaled_adversarial_loss: 0.0705 - val_loss: 0.2196 - val_sparse_categorical_crossentropy: 0.1222 - val_sparse_categorical_accuracy: 0.9554 - val_scaled_adversarial_loss: 0.0974\n",
      "Epoch 478/1000\n",
      "11/11 [==============================] - 4s 327ms/step - loss: 0.1569 - sparse_categorical_crossentropy: 0.0845 - sparse_categorical_accuracy: 0.9714 - scaled_adversarial_loss: 0.0724 - val_loss: 0.2241 - val_sparse_categorical_crossentropy: 0.1273 - val_sparse_categorical_accuracy: 0.9569 - val_scaled_adversarial_loss: 0.0968\n",
      "Epoch 479/1000\n",
      "11/11 [==============================] - 4s 336ms/step - loss: 0.1620 - sparse_categorical_crossentropy: 0.0878 - sparse_categorical_accuracy: 0.9675 - scaled_adversarial_loss: 0.0742 - val_loss: 0.2085 - val_sparse_categorical_crossentropy: 0.1161 - val_sparse_categorical_accuracy: 0.9494 - val_scaled_adversarial_loss: 0.0925\n",
      "Epoch 480/1000\n",
      "11/11 [==============================] - 4s 340ms/step - loss: 0.1673 - sparse_categorical_crossentropy: 0.0922 - sparse_categorical_accuracy: 0.9641 - scaled_adversarial_loss: 0.0752 - val_loss: 0.1996 - val_sparse_categorical_crossentropy: 0.1160 - val_sparse_categorical_accuracy: 0.9546 - val_scaled_adversarial_loss: 0.0836\n",
      "Epoch 481/1000\n",
      "11/11 [==============================] - 4s 332ms/step - loss: 0.1659 - sparse_categorical_crossentropy: 0.0927 - sparse_categorical_accuracy: 0.9678 - scaled_adversarial_loss: 0.0732 - val_loss: 0.2030 - val_sparse_categorical_crossentropy: 0.1165 - val_sparse_categorical_accuracy: 0.9561 - val_scaled_adversarial_loss: 0.0865\n",
      "Epoch 482/1000\n",
      "11/11 [==============================] - 4s 330ms/step - loss: 0.1668 - sparse_categorical_crossentropy: 0.0939 - sparse_categorical_accuracy: 0.9673 - scaled_adversarial_loss: 0.0730 - val_loss: 0.1944 - val_sparse_categorical_crossentropy: 0.1191 - val_sparse_categorical_accuracy: 0.9539 - val_scaled_adversarial_loss: 0.0752\n",
      "Epoch 483/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.1649 - sparse_categorical_crossentropy: 0.0903 - sparse_categorical_accuracy: 0.9712 - scaled_adversarial_loss: 0.0746 - val_loss: 0.1935 - val_sparse_categorical_crossentropy: 0.1110 - val_sparse_categorical_accuracy: 0.9554 - val_scaled_adversarial_loss: 0.0825\n",
      "Epoch 484/1000\n",
      "11/11 [==============================] - 4s 331ms/step - loss: 0.1572 - sparse_categorical_crossentropy: 0.0850 - sparse_categorical_accuracy: 0.9693 - scaled_adversarial_loss: 0.0722 - val_loss: 0.1986 - val_sparse_categorical_crossentropy: 0.1166 - val_sparse_categorical_accuracy: 0.9517 - val_scaled_adversarial_loss: 0.0820\n",
      "Epoch 485/1000\n",
      "11/11 [==============================] - 4s 331ms/step - loss: 0.1561 - sparse_categorical_crossentropy: 0.0850 - sparse_categorical_accuracy: 0.9704 - scaled_adversarial_loss: 0.0711 - val_loss: 0.1956 - val_sparse_categorical_crossentropy: 0.1144 - val_sparse_categorical_accuracy: 0.9554 - val_scaled_adversarial_loss: 0.0812\n",
      "Epoch 486/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.1581 - sparse_categorical_crossentropy: 0.0844 - sparse_categorical_accuracy: 0.9699 - scaled_adversarial_loss: 0.0737 - val_loss: 0.2044 - val_sparse_categorical_crossentropy: 0.1195 - val_sparse_categorical_accuracy: 0.9554 - val_scaled_adversarial_loss: 0.0849\n",
      "Epoch 487/1000\n",
      "11/11 [==============================] - 4s 330ms/step - loss: 0.1578 - sparse_categorical_crossentropy: 0.0866 - sparse_categorical_accuracy: 0.9676 - scaled_adversarial_loss: 0.0712 - val_loss: 0.2000 - val_sparse_categorical_crossentropy: 0.1089 - val_sparse_categorical_accuracy: 0.9584 - val_scaled_adversarial_loss: 0.0912\n",
      "Epoch 488/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.1564 - sparse_categorical_crossentropy: 0.0857 - sparse_categorical_accuracy: 0.9688 - scaled_adversarial_loss: 0.0707 - val_loss: 0.1917 - val_sparse_categorical_crossentropy: 0.1122 - val_sparse_categorical_accuracy: 0.9532 - val_scaled_adversarial_loss: 0.0795\n",
      "Epoch 489/1000\n",
      "11/11 [==============================] - 4s 328ms/step - loss: 0.1621 - sparse_categorical_crossentropy: 0.0882 - sparse_categorical_accuracy: 0.9676 - scaled_adversarial_loss: 0.0739 - val_loss: 0.2024 - val_sparse_categorical_crossentropy: 0.1212 - val_sparse_categorical_accuracy: 0.9465 - val_scaled_adversarial_loss: 0.0812\n",
      "Epoch 490/1000\n",
      "11/11 [==============================] - 4s 343ms/step - loss: 0.1645 - sparse_categorical_crossentropy: 0.0923 - sparse_categorical_accuracy: 0.9675 - scaled_adversarial_loss: 0.0723 - val_loss: 0.2145 - val_sparse_categorical_crossentropy: 0.1184 - val_sparse_categorical_accuracy: 0.9472 - val_scaled_adversarial_loss: 0.0961\n",
      "Epoch 491/1000\n",
      "11/11 [==============================] - 4s 329ms/step - loss: 0.1643 - sparse_categorical_crossentropy: 0.0894 - sparse_categorical_accuracy: 0.9675 - scaled_adversarial_loss: 0.0749 - val_loss: 0.2212 - val_sparse_categorical_crossentropy: 0.1276 - val_sparse_categorical_accuracy: 0.9480 - val_scaled_adversarial_loss: 0.0936\n",
      "Epoch 492/1000\n",
      "11/11 [==============================] - 4s 330ms/step - loss: 0.1640 - sparse_categorical_crossentropy: 0.0925 - sparse_categorical_accuracy: 0.9680 - scaled_adversarial_loss: 0.0714 - val_loss: 0.2122 - val_sparse_categorical_crossentropy: 0.1220 - val_sparse_categorical_accuracy: 0.9569 - val_scaled_adversarial_loss: 0.0902\n",
      "Epoch 493/1000\n",
      "11/11 [==============================] - 4s 328ms/step - loss: 0.1600 - sparse_categorical_crossentropy: 0.0878 - sparse_categorical_accuracy: 0.9678 - scaled_adversarial_loss: 0.0722 - val_loss: 0.2026 - val_sparse_categorical_crossentropy: 0.1167 - val_sparse_categorical_accuracy: 0.9584 - val_scaled_adversarial_loss: 0.0859\n",
      "Epoch 494/1000\n",
      "11/11 [==============================] - 4s 328ms/step - loss: 0.1593 - sparse_categorical_crossentropy: 0.0898 - sparse_categorical_accuracy: 0.9714 - scaled_adversarial_loss: 0.0696 - val_loss: 0.2037 - val_sparse_categorical_crossentropy: 0.1106 - val_sparse_categorical_accuracy: 0.9546 - val_scaled_adversarial_loss: 0.0931\n",
      "Epoch 495/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.1518 - sparse_categorical_crossentropy: 0.0805 - sparse_categorical_accuracy: 0.9706 - scaled_adversarial_loss: 0.0714 - val_loss: 0.2121 - val_sparse_categorical_crossentropy: 0.1224 - val_sparse_categorical_accuracy: 0.9569 - val_scaled_adversarial_loss: 0.0897\n",
      "Epoch 496/1000\n",
      "11/11 [==============================] - 4s 330ms/step - loss: 0.1585 - sparse_categorical_crossentropy: 0.0877 - sparse_categorical_accuracy: 0.9684 - scaled_adversarial_loss: 0.0708 - val_loss: 0.2100 - val_sparse_categorical_crossentropy: 0.1295 - val_sparse_categorical_accuracy: 0.9494 - val_scaled_adversarial_loss: 0.0805\n",
      "Epoch 497/1000\n",
      "11/11 [==============================] - 4s 331ms/step - loss: 0.1599 - sparse_categorical_crossentropy: 0.0907 - sparse_categorical_accuracy: 0.9656 - scaled_adversarial_loss: 0.0692 - val_loss: 0.2426 - val_sparse_categorical_crossentropy: 0.1269 - val_sparse_categorical_accuracy: 0.9539 - val_scaled_adversarial_loss: 0.1157\n",
      "Epoch 498/1000\n",
      "11/11 [==============================] - 4s 332ms/step - loss: 0.1554 - sparse_categorical_crossentropy: 0.0846 - sparse_categorical_accuracy: 0.9725 - scaled_adversarial_loss: 0.0708 - val_loss: 0.2107 - val_sparse_categorical_crossentropy: 0.1198 - val_sparse_categorical_accuracy: 0.9509 - val_scaled_adversarial_loss: 0.0909\n",
      "Epoch 499/1000\n",
      "11/11 [==============================] - 4s 329ms/step - loss: 0.1579 - sparse_categorical_crossentropy: 0.0856 - sparse_categorical_accuracy: 0.9675 - scaled_adversarial_loss: 0.0723 - val_loss: 0.2051 - val_sparse_categorical_crossentropy: 0.1114 - val_sparse_categorical_accuracy: 0.9576 - val_scaled_adversarial_loss: 0.0937\n",
      "Epoch 500/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.1485 - sparse_categorical_crossentropy: 0.0786 - sparse_categorical_accuracy: 0.9702 - scaled_adversarial_loss: 0.0699 - val_loss: 0.2053 - val_sparse_categorical_crossentropy: 0.1155 - val_sparse_categorical_accuracy: 0.9509 - val_scaled_adversarial_loss: 0.0898\n",
      "Epoch 501/1000\n",
      "11/11 [==============================] - 4s 330ms/step - loss: 0.1577 - sparse_categorical_crossentropy: 0.0892 - sparse_categorical_accuracy: 0.9686 - scaled_adversarial_loss: 0.0685 - val_loss: 0.2187 - val_sparse_categorical_crossentropy: 0.1173 - val_sparse_categorical_accuracy: 0.9539 - val_scaled_adversarial_loss: 0.1014\n",
      "Epoch 502/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.1559 - sparse_categorical_crossentropy: 0.0813 - sparse_categorical_accuracy: 0.9710 - scaled_adversarial_loss: 0.0747 - val_loss: 0.2057 - val_sparse_categorical_crossentropy: 0.1179 - val_sparse_categorical_accuracy: 0.9584 - val_scaled_adversarial_loss: 0.0878\n",
      "Epoch 503/1000\n",
      "11/11 [==============================] - 4s 332ms/step - loss: 0.1494 - sparse_categorical_crossentropy: 0.0812 - sparse_categorical_accuracy: 0.9719 - scaled_adversarial_loss: 0.0683 - val_loss: 0.1904 - val_sparse_categorical_crossentropy: 0.1064 - val_sparse_categorical_accuracy: 0.9532 - val_scaled_adversarial_loss: 0.0839\n",
      "Epoch 504/1000\n",
      "11/11 [==============================] - 4s 328ms/step - loss: 0.1615 - sparse_categorical_crossentropy: 0.0910 - sparse_categorical_accuracy: 0.9682 - scaled_adversarial_loss: 0.0704 - val_loss: 0.1883 - val_sparse_categorical_crossentropy: 0.1123 - val_sparse_categorical_accuracy: 0.9561 - val_scaled_adversarial_loss: 0.0760\n",
      "Epoch 505/1000\n",
      "11/11 [==============================] - 4s 327ms/step - loss: 0.1534 - sparse_categorical_crossentropy: 0.0859 - sparse_categorical_accuracy: 0.9691 - scaled_adversarial_loss: 0.0675 - val_loss: 0.1993 - val_sparse_categorical_crossentropy: 0.1152 - val_sparse_categorical_accuracy: 0.9524 - val_scaled_adversarial_loss: 0.0841\n",
      "Epoch 506/1000\n",
      "11/11 [==============================] - 4s 332ms/step - loss: 0.1542 - sparse_categorical_crossentropy: 0.0813 - sparse_categorical_accuracy: 0.9721 - scaled_adversarial_loss: 0.0728 - val_loss: 0.1954 - val_sparse_categorical_crossentropy: 0.1154 - val_sparse_categorical_accuracy: 0.9561 - val_scaled_adversarial_loss: 0.0799\n",
      "Epoch 507/1000\n",
      "11/11 [==============================] - 4s 331ms/step - loss: 0.1558 - sparse_categorical_crossentropy: 0.0844 - sparse_categorical_accuracy: 0.9686 - scaled_adversarial_loss: 0.0714 - val_loss: 0.1934 - val_sparse_categorical_crossentropy: 0.1085 - val_sparse_categorical_accuracy: 0.9561 - val_scaled_adversarial_loss: 0.0849\n",
      "Epoch 508/1000\n",
      "11/11 [==============================] - 4s 331ms/step - loss: 0.1529 - sparse_categorical_crossentropy: 0.0842 - sparse_categorical_accuracy: 0.9734 - scaled_adversarial_loss: 0.0687 - val_loss: 0.2046 - val_sparse_categorical_crossentropy: 0.1115 - val_sparse_categorical_accuracy: 0.9532 - val_scaled_adversarial_loss: 0.0931\n",
      "Epoch 509/1000\n",
      "11/11 [==============================] - 4s 331ms/step - loss: 0.1633 - sparse_categorical_crossentropy: 0.0899 - sparse_categorical_accuracy: 0.9654 - scaled_adversarial_loss: 0.0734 - val_loss: 0.2013 - val_sparse_categorical_crossentropy: 0.1121 - val_sparse_categorical_accuracy: 0.9554 - val_scaled_adversarial_loss: 0.0892\n",
      "Epoch 510/1000\n",
      "11/11 [==============================] - 4s 332ms/step - loss: 0.1591 - sparse_categorical_crossentropy: 0.0881 - sparse_categorical_accuracy: 0.9662 - scaled_adversarial_loss: 0.0710 - val_loss: 0.1905 - val_sparse_categorical_crossentropy: 0.1077 - val_sparse_categorical_accuracy: 0.9569 - val_scaled_adversarial_loss: 0.0829\n",
      "Epoch 511/1000\n",
      "11/11 [==============================] - 4s 329ms/step - loss: 0.1612 - sparse_categorical_crossentropy: 0.0905 - sparse_categorical_accuracy: 0.9669 - scaled_adversarial_loss: 0.0707 - val_loss: 0.1996 - val_sparse_categorical_crossentropy: 0.1156 - val_sparse_categorical_accuracy: 0.9576 - val_scaled_adversarial_loss: 0.0840\n",
      "Epoch 512/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.1551 - sparse_categorical_crossentropy: 0.0848 - sparse_categorical_accuracy: 0.9688 - scaled_adversarial_loss: 0.0703 - val_loss: 0.1909 - val_sparse_categorical_crossentropy: 0.1091 - val_sparse_categorical_accuracy: 0.9569 - val_scaled_adversarial_loss: 0.0818\n",
      "Epoch 513/1000\n",
      "11/11 [==============================] - 4s 331ms/step - loss: 0.1520 - sparse_categorical_crossentropy: 0.0825 - sparse_categorical_accuracy: 0.9708 - scaled_adversarial_loss: 0.0694 - val_loss: 0.2041 - val_sparse_categorical_crossentropy: 0.1126 - val_sparse_categorical_accuracy: 0.9569 - val_scaled_adversarial_loss: 0.0915\n",
      "Epoch 514/1000\n",
      "11/11 [==============================] - 4s 332ms/step - loss: 0.1545 - sparse_categorical_crossentropy: 0.0849 - sparse_categorical_accuracy: 0.9697 - scaled_adversarial_loss: 0.0696 - val_loss: 0.1929 - val_sparse_categorical_crossentropy: 0.1081 - val_sparse_categorical_accuracy: 0.9584 - val_scaled_adversarial_loss: 0.0849\n",
      "Epoch 515/1000\n",
      "11/11 [==============================] - 4s 329ms/step - loss: 0.1601 - sparse_categorical_crossentropy: 0.0889 - sparse_categorical_accuracy: 0.9675 - scaled_adversarial_loss: 0.0712 - val_loss: 0.1871 - val_sparse_categorical_crossentropy: 0.1084 - val_sparse_categorical_accuracy: 0.9569 - val_scaled_adversarial_loss: 0.0787\n",
      "Epoch 516/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.1571 - sparse_categorical_crossentropy: 0.0862 - sparse_categorical_accuracy: 0.9695 - scaled_adversarial_loss: 0.0709 - val_loss: 0.1901 - val_sparse_categorical_crossentropy: 0.1084 - val_sparse_categorical_accuracy: 0.9576 - val_scaled_adversarial_loss: 0.0817\n",
      "Epoch 517/1000\n",
      "11/11 [==============================] - 4s 332ms/step - loss: 0.1638 - sparse_categorical_crossentropy: 0.0927 - sparse_categorical_accuracy: 0.9673 - scaled_adversarial_loss: 0.0711 - val_loss: 0.2062 - val_sparse_categorical_crossentropy: 0.1110 - val_sparse_categorical_accuracy: 0.9569 - val_scaled_adversarial_loss: 0.0952\n",
      "Epoch 518/1000\n",
      "11/11 [==============================] - 4s 329ms/step - loss: 0.1555 - sparse_categorical_crossentropy: 0.0838 - sparse_categorical_accuracy: 0.9704 - scaled_adversarial_loss: 0.0718 - val_loss: 0.2030 - val_sparse_categorical_crossentropy: 0.1128 - val_sparse_categorical_accuracy: 0.9554 - val_scaled_adversarial_loss: 0.0902\n",
      "Epoch 519/1000\n",
      "11/11 [==============================] - 4s 330ms/step - loss: 0.1528 - sparse_categorical_crossentropy: 0.0831 - sparse_categorical_accuracy: 0.9702 - scaled_adversarial_loss: 0.0697 - val_loss: 0.2055 - val_sparse_categorical_crossentropy: 0.1121 - val_sparse_categorical_accuracy: 0.9524 - val_scaled_adversarial_loss: 0.0934\n",
      "Epoch 520/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.1516 - sparse_categorical_crossentropy: 0.0799 - sparse_categorical_accuracy: 0.9701 - scaled_adversarial_loss: 0.0716 - val_loss: 0.2140 - val_sparse_categorical_crossentropy: 0.1225 - val_sparse_categorical_accuracy: 0.9539 - val_scaled_adversarial_loss: 0.0915\n",
      "Epoch 521/1000\n",
      "11/11 [==============================] - 4s 338ms/step - loss: 0.1579 - sparse_categorical_crossentropy: 0.0857 - sparse_categorical_accuracy: 0.9706 - scaled_adversarial_loss: 0.0722 - val_loss: 0.2138 - val_sparse_categorical_crossentropy: 0.1164 - val_sparse_categorical_accuracy: 0.9554 - val_scaled_adversarial_loss: 0.0974\n",
      "Epoch 522/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.1538 - sparse_categorical_crossentropy: 0.0828 - sparse_categorical_accuracy: 0.9702 - scaled_adversarial_loss: 0.0710 - val_loss: 0.2039 - val_sparse_categorical_crossentropy: 0.1177 - val_sparse_categorical_accuracy: 0.9591 - val_scaled_adversarial_loss: 0.0862\n",
      "Epoch 523/1000\n",
      "11/11 [==============================] - 4s 331ms/step - loss: 0.1547 - sparse_categorical_crossentropy: 0.0845 - sparse_categorical_accuracy: 0.9695 - scaled_adversarial_loss: 0.0702 - val_loss: 0.1916 - val_sparse_categorical_crossentropy: 0.1106 - val_sparse_categorical_accuracy: 0.9561 - val_scaled_adversarial_loss: 0.0809\n",
      "Epoch 524/1000\n",
      "11/11 [==============================] - 4s 328ms/step - loss: 0.1545 - sparse_categorical_crossentropy: 0.0845 - sparse_categorical_accuracy: 0.9686 - scaled_adversarial_loss: 0.0700 - val_loss: 0.2086 - val_sparse_categorical_crossentropy: 0.1163 - val_sparse_categorical_accuracy: 0.9554 - val_scaled_adversarial_loss: 0.0923\n",
      "Epoch 525/1000\n",
      "11/11 [==============================] - 4s 331ms/step - loss: 0.1535 - sparse_categorical_crossentropy: 0.0837 - sparse_categorical_accuracy: 0.9682 - scaled_adversarial_loss: 0.0698 - val_loss: 0.2288 - val_sparse_categorical_crossentropy: 0.1241 - val_sparse_categorical_accuracy: 0.9517 - val_scaled_adversarial_loss: 0.1047\n",
      "Epoch 526/1000\n",
      "11/11 [==============================] - 4s 331ms/step - loss: 0.1547 - sparse_categorical_crossentropy: 0.0805 - sparse_categorical_accuracy: 0.9704 - scaled_adversarial_loss: 0.0742 - val_loss: 0.2116 - val_sparse_categorical_crossentropy: 0.1243 - val_sparse_categorical_accuracy: 0.9554 - val_scaled_adversarial_loss: 0.0874\n",
      "Epoch 527/1000\n",
      "11/11 [==============================] - 4s 332ms/step - loss: 0.1462 - sparse_categorical_crossentropy: 0.0795 - sparse_categorical_accuracy: 0.9704 - scaled_adversarial_loss: 0.0667 - val_loss: 0.2039 - val_sparse_categorical_crossentropy: 0.1137 - val_sparse_categorical_accuracy: 0.9546 - val_scaled_adversarial_loss: 0.0902\n",
      "Epoch 528/1000\n",
      "11/11 [==============================] - 4s 330ms/step - loss: 0.1586 - sparse_categorical_crossentropy: 0.0854 - sparse_categorical_accuracy: 0.9723 - scaled_adversarial_loss: 0.0733 - val_loss: 0.1945 - val_sparse_categorical_crossentropy: 0.1083 - val_sparse_categorical_accuracy: 0.9576 - val_scaled_adversarial_loss: 0.0862\n",
      "Epoch 529/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.1523 - sparse_categorical_crossentropy: 0.0819 - sparse_categorical_accuracy: 0.9704 - scaled_adversarial_loss: 0.0703 - val_loss: 0.1901 - val_sparse_categorical_crossentropy: 0.1106 - val_sparse_categorical_accuracy: 0.9561 - val_scaled_adversarial_loss: 0.0795\n",
      "Epoch 530/1000\n",
      "11/11 [==============================] - 4s 336ms/step - loss: 0.1588 - sparse_categorical_crossentropy: 0.0826 - sparse_categorical_accuracy: 0.9717 - scaled_adversarial_loss: 0.0763 - val_loss: 0.1927 - val_sparse_categorical_crossentropy: 0.1118 - val_sparse_categorical_accuracy: 0.9561 - val_scaled_adversarial_loss: 0.0809\n",
      "Epoch 531/1000\n",
      "11/11 [==============================] - 4s 335ms/step - loss: 0.1606 - sparse_categorical_crossentropy: 0.0894 - sparse_categorical_accuracy: 0.9682 - scaled_adversarial_loss: 0.0712 - val_loss: 0.2128 - val_sparse_categorical_crossentropy: 0.1217 - val_sparse_categorical_accuracy: 0.9561 - val_scaled_adversarial_loss: 0.0911\n",
      "Epoch 532/1000\n",
      "11/11 [==============================] - 4s 347ms/step - loss: 0.1572 - sparse_categorical_crossentropy: 0.0867 - sparse_categorical_accuracy: 0.9688 - scaled_adversarial_loss: 0.0705 - val_loss: 0.2220 - val_sparse_categorical_crossentropy: 0.1289 - val_sparse_categorical_accuracy: 0.9561 - val_scaled_adversarial_loss: 0.0931\n",
      "Epoch 533/1000\n",
      "11/11 [==============================] - 4s 338ms/step - loss: 0.1495 - sparse_categorical_crossentropy: 0.0816 - sparse_categorical_accuracy: 0.9704 - scaled_adversarial_loss: 0.0679 - val_loss: 0.2045 - val_sparse_categorical_crossentropy: 0.1111 - val_sparse_categorical_accuracy: 0.9591 - val_scaled_adversarial_loss: 0.0933\n",
      "Epoch 534/1000\n",
      "11/11 [==============================] - 4s 335ms/step - loss: 0.1561 - sparse_categorical_crossentropy: 0.0821 - sparse_categorical_accuracy: 0.9702 - scaled_adversarial_loss: 0.0740 - val_loss: 0.2185 - val_sparse_categorical_crossentropy: 0.1214 - val_sparse_categorical_accuracy: 0.9576 - val_scaled_adversarial_loss: 0.0971\n",
      "Epoch 535/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.1497 - sparse_categorical_crossentropy: 0.0813 - sparse_categorical_accuracy: 0.9699 - scaled_adversarial_loss: 0.0684 - val_loss: 0.2325 - val_sparse_categorical_crossentropy: 0.1282 - val_sparse_categorical_accuracy: 0.9569 - val_scaled_adversarial_loss: 0.1044\n",
      "Epoch 536/1000\n",
      "11/11 [==============================] - 4s 330ms/step - loss: 0.1530 - sparse_categorical_crossentropy: 0.0810 - sparse_categorical_accuracy: 0.9714 - scaled_adversarial_loss: 0.0720 - val_loss: 0.2151 - val_sparse_categorical_crossentropy: 0.1240 - val_sparse_categorical_accuracy: 0.9561 - val_scaled_adversarial_loss: 0.0912\n",
      "Epoch 537/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.1494 - sparse_categorical_crossentropy: 0.0796 - sparse_categorical_accuracy: 0.9706 - scaled_adversarial_loss: 0.0698 - val_loss: 0.2109 - val_sparse_categorical_crossentropy: 0.1203 - val_sparse_categorical_accuracy: 0.9539 - val_scaled_adversarial_loss: 0.0906\n",
      "Epoch 538/1000\n",
      "11/11 [==============================] - 4s 337ms/step - loss: 0.1574 - sparse_categorical_crossentropy: 0.0866 - sparse_categorical_accuracy: 0.9684 - scaled_adversarial_loss: 0.0708 - val_loss: 0.2062 - val_sparse_categorical_crossentropy: 0.1198 - val_sparse_categorical_accuracy: 0.9584 - val_scaled_adversarial_loss: 0.0864\n",
      "Epoch 539/1000\n",
      "11/11 [==============================] - 4s 336ms/step - loss: 0.1474 - sparse_categorical_crossentropy: 0.0807 - sparse_categorical_accuracy: 0.9699 - scaled_adversarial_loss: 0.0667 - val_loss: 0.1892 - val_sparse_categorical_crossentropy: 0.1059 - val_sparse_categorical_accuracy: 0.9591 - val_scaled_adversarial_loss: 0.0833\n",
      "Epoch 540/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.1498 - sparse_categorical_crossentropy: 0.0810 - sparse_categorical_accuracy: 0.9686 - scaled_adversarial_loss: 0.0688 - val_loss: 0.1982 - val_sparse_categorical_crossentropy: 0.1129 - val_sparse_categorical_accuracy: 0.9546 - val_scaled_adversarial_loss: 0.0853\n",
      "Epoch 541/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.1541 - sparse_categorical_crossentropy: 0.0829 - sparse_categorical_accuracy: 0.9712 - scaled_adversarial_loss: 0.0712 - val_loss: 0.2130 - val_sparse_categorical_crossentropy: 0.1227 - val_sparse_categorical_accuracy: 0.9561 - val_scaled_adversarial_loss: 0.0903\n",
      "Epoch 542/1000\n",
      "11/11 [==============================] - 4s 332ms/step - loss: 0.1481 - sparse_categorical_crossentropy: 0.0778 - sparse_categorical_accuracy: 0.9710 - scaled_adversarial_loss: 0.0703 - val_loss: 0.2180 - val_sparse_categorical_crossentropy: 0.1167 - val_sparse_categorical_accuracy: 0.9576 - val_scaled_adversarial_loss: 0.1013\n",
      "Epoch 543/1000\n",
      "11/11 [==============================] - 4s 336ms/step - loss: 0.1451 - sparse_categorical_crossentropy: 0.0750 - sparse_categorical_accuracy: 0.9730 - scaled_adversarial_loss: 0.0701 - val_loss: 0.2181 - val_sparse_categorical_crossentropy: 0.1222 - val_sparse_categorical_accuracy: 0.9584 - val_scaled_adversarial_loss: 0.0959\n",
      "Epoch 544/1000\n",
      "11/11 [==============================] - 4s 335ms/step - loss: 0.1444 - sparse_categorical_crossentropy: 0.0752 - sparse_categorical_accuracy: 0.9721 - scaled_adversarial_loss: 0.0692 - val_loss: 0.1908 - val_sparse_categorical_crossentropy: 0.1126 - val_sparse_categorical_accuracy: 0.9599 - val_scaled_adversarial_loss: 0.0782\n",
      "Epoch 545/1000\n",
      "11/11 [==============================] - 4s 335ms/step - loss: 0.1509 - sparse_categorical_crossentropy: 0.0813 - sparse_categorical_accuracy: 0.9734 - scaled_adversarial_loss: 0.0696 - val_loss: 0.2022 - val_sparse_categorical_crossentropy: 0.1182 - val_sparse_categorical_accuracy: 0.9561 - val_scaled_adversarial_loss: 0.0839\n",
      "Epoch 546/1000\n",
      "11/11 [==============================] - 4s 336ms/step - loss: 0.1493 - sparse_categorical_crossentropy: 0.0839 - sparse_categorical_accuracy: 0.9701 - scaled_adversarial_loss: 0.0654 - val_loss: 0.1927 - val_sparse_categorical_crossentropy: 0.1138 - val_sparse_categorical_accuracy: 0.9584 - val_scaled_adversarial_loss: 0.0790\n",
      "Epoch 547/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.1528 - sparse_categorical_crossentropy: 0.0816 - sparse_categorical_accuracy: 0.9701 - scaled_adversarial_loss: 0.0712 - val_loss: 0.1999 - val_sparse_categorical_crossentropy: 0.1157 - val_sparse_categorical_accuracy: 0.9591 - val_scaled_adversarial_loss: 0.0843\n",
      "Epoch 548/1000\n",
      "11/11 [==============================] - 4s 337ms/step - loss: 0.1491 - sparse_categorical_crossentropy: 0.0819 - sparse_categorical_accuracy: 0.9682 - scaled_adversarial_loss: 0.0673 - val_loss: 0.2162 - val_sparse_categorical_crossentropy: 0.1190 - val_sparse_categorical_accuracy: 0.9599 - val_scaled_adversarial_loss: 0.0971\n",
      "Epoch 549/1000\n",
      "11/11 [==============================] - 4s 342ms/step - loss: 0.1451 - sparse_categorical_crossentropy: 0.0771 - sparse_categorical_accuracy: 0.9736 - scaled_adversarial_loss: 0.0680 - val_loss: 0.2120 - val_sparse_categorical_crossentropy: 0.1212 - val_sparse_categorical_accuracy: 0.9576 - val_scaled_adversarial_loss: 0.0908\n",
      "Epoch 550/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.1482 - sparse_categorical_crossentropy: 0.0762 - sparse_categorical_accuracy: 0.9725 - scaled_adversarial_loss: 0.0720 - val_loss: 0.2125 - val_sparse_categorical_crossentropy: 0.1144 - val_sparse_categorical_accuracy: 0.9591 - val_scaled_adversarial_loss: 0.0981\n",
      "Epoch 551/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.1483 - sparse_categorical_crossentropy: 0.0794 - sparse_categorical_accuracy: 0.9730 - scaled_adversarial_loss: 0.0689 - val_loss: 0.1903 - val_sparse_categorical_crossentropy: 0.1068 - val_sparse_categorical_accuracy: 0.9591 - val_scaled_adversarial_loss: 0.0835\n",
      "Epoch 552/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.1531 - sparse_categorical_crossentropy: 0.0810 - sparse_categorical_accuracy: 0.9716 - scaled_adversarial_loss: 0.0721 - val_loss: 0.1960 - val_sparse_categorical_crossentropy: 0.1166 - val_sparse_categorical_accuracy: 0.9584 - val_scaled_adversarial_loss: 0.0794\n",
      "Epoch 553/1000\n",
      "11/11 [==============================] - 4s 335ms/step - loss: 0.1432 - sparse_categorical_crossentropy: 0.0773 - sparse_categorical_accuracy: 0.9730 - scaled_adversarial_loss: 0.0659 - val_loss: 0.2042 - val_sparse_categorical_crossentropy: 0.1163 - val_sparse_categorical_accuracy: 0.9561 - val_scaled_adversarial_loss: 0.0879\n",
      "Epoch 554/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.1537 - sparse_categorical_crossentropy: 0.0831 - sparse_categorical_accuracy: 0.9702 - scaled_adversarial_loss: 0.0705 - val_loss: 0.2027 - val_sparse_categorical_crossentropy: 0.1158 - val_sparse_categorical_accuracy: 0.9569 - val_scaled_adversarial_loss: 0.0868\n",
      "Epoch 555/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.1530 - sparse_categorical_crossentropy: 0.0800 - sparse_categorical_accuracy: 0.9710 - scaled_adversarial_loss: 0.0730 - val_loss: 0.1954 - val_sparse_categorical_crossentropy: 0.1121 - val_sparse_categorical_accuracy: 0.9569 - val_scaled_adversarial_loss: 0.0833\n",
      "Epoch 556/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.1455 - sparse_categorical_crossentropy: 0.0754 - sparse_categorical_accuracy: 0.9727 - scaled_adversarial_loss: 0.0701 - val_loss: 0.2028 - val_sparse_categorical_crossentropy: 0.1118 - val_sparse_categorical_accuracy: 0.9591 - val_scaled_adversarial_loss: 0.0910\n",
      "Epoch 557/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.1428 - sparse_categorical_crossentropy: 0.0731 - sparse_categorical_accuracy: 0.9751 - scaled_adversarial_loss: 0.0697 - val_loss: 0.1828 - val_sparse_categorical_crossentropy: 0.1083 - val_sparse_categorical_accuracy: 0.9539 - val_scaled_adversarial_loss: 0.0745\n",
      "Epoch 558/1000\n",
      "11/11 [==============================] - 4s 330ms/step - loss: 0.1510 - sparse_categorical_crossentropy: 0.0801 - sparse_categorical_accuracy: 0.9704 - scaled_adversarial_loss: 0.0708 - val_loss: 0.1829 - val_sparse_categorical_crossentropy: 0.1061 - val_sparse_categorical_accuracy: 0.9569 - val_scaled_adversarial_loss: 0.0768\n",
      "Epoch 559/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.1522 - sparse_categorical_crossentropy: 0.0817 - sparse_categorical_accuracy: 0.9717 - scaled_adversarial_loss: 0.0705 - val_loss: 0.1843 - val_sparse_categorical_crossentropy: 0.1063 - val_sparse_categorical_accuracy: 0.9561 - val_scaled_adversarial_loss: 0.0781\n",
      "Epoch 560/1000\n",
      "11/11 [==============================] - 4s 335ms/step - loss: 0.1525 - sparse_categorical_crossentropy: 0.0816 - sparse_categorical_accuracy: 0.9719 - scaled_adversarial_loss: 0.0710 - val_loss: 0.1962 - val_sparse_categorical_crossentropy: 0.1111 - val_sparse_categorical_accuracy: 0.9561 - val_scaled_adversarial_loss: 0.0851\n",
      "Epoch 561/1000\n",
      "11/11 [==============================] - 4s 335ms/step - loss: 0.1508 - sparse_categorical_crossentropy: 0.0819 - sparse_categorical_accuracy: 0.9740 - scaled_adversarial_loss: 0.0689 - val_loss: 0.2117 - val_sparse_categorical_crossentropy: 0.1185 - val_sparse_categorical_accuracy: 0.9606 - val_scaled_adversarial_loss: 0.0932\n",
      "Epoch 562/1000\n",
      "11/11 [==============================] - 4s 335ms/step - loss: 0.1476 - sparse_categorical_crossentropy: 0.0802 - sparse_categorical_accuracy: 0.9716 - scaled_adversarial_loss: 0.0674 - val_loss: 0.1904 - val_sparse_categorical_crossentropy: 0.1080 - val_sparse_categorical_accuracy: 0.9569 - val_scaled_adversarial_loss: 0.0824\n",
      "Epoch 563/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.1472 - sparse_categorical_crossentropy: 0.0790 - sparse_categorical_accuracy: 0.9721 - scaled_adversarial_loss: 0.0681 - val_loss: 0.2168 - val_sparse_categorical_crossentropy: 0.1198 - val_sparse_categorical_accuracy: 0.9539 - val_scaled_adversarial_loss: 0.0970\n",
      "Epoch 564/1000\n",
      "11/11 [==============================] - 4s 332ms/step - loss: 0.1509 - sparse_categorical_crossentropy: 0.0803 - sparse_categorical_accuracy: 0.9725 - scaled_adversarial_loss: 0.0706 - val_loss: 0.2097 - val_sparse_categorical_crossentropy: 0.1159 - val_sparse_categorical_accuracy: 0.9532 - val_scaled_adversarial_loss: 0.0939\n",
      "Epoch 565/1000\n",
      "11/11 [==============================] - 4s 332ms/step - loss: 0.1529 - sparse_categorical_crossentropy: 0.0803 - sparse_categorical_accuracy: 0.9686 - scaled_adversarial_loss: 0.0726 - val_loss: 0.2228 - val_sparse_categorical_crossentropy: 0.1275 - val_sparse_categorical_accuracy: 0.9576 - val_scaled_adversarial_loss: 0.0953\n",
      "Epoch 566/1000\n",
      "11/11 [==============================] - 4s 335ms/step - loss: 0.1565 - sparse_categorical_crossentropy: 0.0874 - sparse_categorical_accuracy: 0.9678 - scaled_adversarial_loss: 0.0691 - val_loss: 0.1939 - val_sparse_categorical_crossentropy: 0.1087 - val_sparse_categorical_accuracy: 0.9621 - val_scaled_adversarial_loss: 0.0852\n",
      "Epoch 567/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.1507 - sparse_categorical_crossentropy: 0.0811 - sparse_categorical_accuracy: 0.9712 - scaled_adversarial_loss: 0.0696 - val_loss: 0.1868 - val_sparse_categorical_crossentropy: 0.1052 - val_sparse_categorical_accuracy: 0.9606 - val_scaled_adversarial_loss: 0.0817\n",
      "Epoch 568/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.1629 - sparse_categorical_crossentropy: 0.0910 - sparse_categorical_accuracy: 0.9663 - scaled_adversarial_loss: 0.0719 - val_loss: 0.1887 - val_sparse_categorical_crossentropy: 0.1087 - val_sparse_categorical_accuracy: 0.9569 - val_scaled_adversarial_loss: 0.0800\n",
      "Epoch 569/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.1506 - sparse_categorical_crossentropy: 0.0831 - sparse_categorical_accuracy: 0.9706 - scaled_adversarial_loss: 0.0674 - val_loss: 0.1963 - val_sparse_categorical_crossentropy: 0.1124 - val_sparse_categorical_accuracy: 0.9561 - val_scaled_adversarial_loss: 0.0839\n",
      "Epoch 570/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.1539 - sparse_categorical_crossentropy: 0.0840 - sparse_categorical_accuracy: 0.9716 - scaled_adversarial_loss: 0.0699 - val_loss: 0.2263 - val_sparse_categorical_crossentropy: 0.1244 - val_sparse_categorical_accuracy: 0.9539 - val_scaled_adversarial_loss: 0.1019\n",
      "Epoch 571/1000\n",
      "11/11 [==============================] - 4s 335ms/step - loss: 0.1503 - sparse_categorical_crossentropy: 0.0787 - sparse_categorical_accuracy: 0.9702 - scaled_adversarial_loss: 0.0716 - val_loss: 0.2135 - val_sparse_categorical_crossentropy: 0.1183 - val_sparse_categorical_accuracy: 0.9554 - val_scaled_adversarial_loss: 0.0952\n",
      "Epoch 572/1000\n",
      "11/11 [==============================] - 4s 335ms/step - loss: 0.1481 - sparse_categorical_crossentropy: 0.0785 - sparse_categorical_accuracy: 0.9725 - scaled_adversarial_loss: 0.0696 - val_loss: 0.2346 - val_sparse_categorical_crossentropy: 0.1382 - val_sparse_categorical_accuracy: 0.9539 - val_scaled_adversarial_loss: 0.0964\n",
      "Epoch 573/1000\n",
      "11/11 [==============================] - 4s 335ms/step - loss: 0.1539 - sparse_categorical_crossentropy: 0.0824 - sparse_categorical_accuracy: 0.9702 - scaled_adversarial_loss: 0.0715 - val_loss: 0.1894 - val_sparse_categorical_crossentropy: 0.1098 - val_sparse_categorical_accuracy: 0.9613 - val_scaled_adversarial_loss: 0.0796\n",
      "Epoch 574/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.1497 - sparse_categorical_crossentropy: 0.0819 - sparse_categorical_accuracy: 0.9729 - scaled_adversarial_loss: 0.0678 - val_loss: 0.2167 - val_sparse_categorical_crossentropy: 0.1249 - val_sparse_categorical_accuracy: 0.9539 - val_scaled_adversarial_loss: 0.0918\n",
      "Epoch 575/1000\n",
      "11/11 [==============================] - 4s 332ms/step - loss: 0.1518 - sparse_categorical_crossentropy: 0.0814 - sparse_categorical_accuracy: 0.9729 - scaled_adversarial_loss: 0.0704 - val_loss: 0.1915 - val_sparse_categorical_crossentropy: 0.1096 - val_sparse_categorical_accuracy: 0.9576 - val_scaled_adversarial_loss: 0.0819\n",
      "Epoch 576/1000\n",
      "11/11 [==============================] - 4s 342ms/step - loss: 0.1476 - sparse_categorical_crossentropy: 0.0838 - sparse_categorical_accuracy: 0.9688 - scaled_adversarial_loss: 0.0638 - val_loss: 0.1942 - val_sparse_categorical_crossentropy: 0.1097 - val_sparse_categorical_accuracy: 0.9576 - val_scaled_adversarial_loss: 0.0844\n",
      "Epoch 577/1000\n",
      "11/11 [==============================] - 4s 341ms/step - loss: 0.1487 - sparse_categorical_crossentropy: 0.0798 - sparse_categorical_accuracy: 0.9734 - scaled_adversarial_loss: 0.0689 - val_loss: 0.2147 - val_sparse_categorical_crossentropy: 0.1224 - val_sparse_categorical_accuracy: 0.9569 - val_scaled_adversarial_loss: 0.0923\n",
      "Epoch 578/1000\n",
      "11/11 [==============================] - 4s 338ms/step - loss: 0.1437 - sparse_categorical_crossentropy: 0.0744 - sparse_categorical_accuracy: 0.9747 - scaled_adversarial_loss: 0.0692 - val_loss: 0.1959 - val_sparse_categorical_crossentropy: 0.1156 - val_sparse_categorical_accuracy: 0.9569 - val_scaled_adversarial_loss: 0.0803\n",
      "Epoch 579/1000\n",
      "11/11 [==============================] - 4s 337ms/step - loss: 0.1509 - sparse_categorical_crossentropy: 0.0821 - sparse_categorical_accuracy: 0.9693 - scaled_adversarial_loss: 0.0687 - val_loss: 0.2054 - val_sparse_categorical_crossentropy: 0.1159 - val_sparse_categorical_accuracy: 0.9561 - val_scaled_adversarial_loss: 0.0894\n",
      "Epoch 580/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.1448 - sparse_categorical_crossentropy: 0.0767 - sparse_categorical_accuracy: 0.9721 - scaled_adversarial_loss: 0.0681 - val_loss: 0.1840 - val_sparse_categorical_crossentropy: 0.1072 - val_sparse_categorical_accuracy: 0.9576 - val_scaled_adversarial_loss: 0.0768\n",
      "Epoch 581/1000\n",
      "11/11 [==============================] - 4s 336ms/step - loss: 0.1412 - sparse_categorical_crossentropy: 0.0741 - sparse_categorical_accuracy: 0.9745 - scaled_adversarial_loss: 0.0672 - val_loss: 0.1948 - val_sparse_categorical_crossentropy: 0.1114 - val_sparse_categorical_accuracy: 0.9606 - val_scaled_adversarial_loss: 0.0834\n",
      "Epoch 582/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.1389 - sparse_categorical_crossentropy: 0.0724 - sparse_categorical_accuracy: 0.9742 - scaled_adversarial_loss: 0.0666 - val_loss: 0.2131 - val_sparse_categorical_crossentropy: 0.1160 - val_sparse_categorical_accuracy: 0.9584 - val_scaled_adversarial_loss: 0.0970\n",
      "Epoch 583/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.1486 - sparse_categorical_crossentropy: 0.0789 - sparse_categorical_accuracy: 0.9716 - scaled_adversarial_loss: 0.0697 - val_loss: 0.2133 - val_sparse_categorical_crossentropy: 0.1239 - val_sparse_categorical_accuracy: 0.9554 - val_scaled_adversarial_loss: 0.0894\n",
      "Epoch 584/1000\n",
      "11/11 [==============================] - 4s 332ms/step - loss: 0.1517 - sparse_categorical_crossentropy: 0.0832 - sparse_categorical_accuracy: 0.9693 - scaled_adversarial_loss: 0.0685 - val_loss: 0.1837 - val_sparse_categorical_crossentropy: 0.1069 - val_sparse_categorical_accuracy: 0.9561 - val_scaled_adversarial_loss: 0.0768\n",
      "Epoch 585/1000\n",
      "11/11 [==============================] - 4s 329ms/step - loss: 0.1435 - sparse_categorical_crossentropy: 0.0775 - sparse_categorical_accuracy: 0.9730 - scaled_adversarial_loss: 0.0660 - val_loss: 0.1908 - val_sparse_categorical_crossentropy: 0.1085 - val_sparse_categorical_accuracy: 0.9569 - val_scaled_adversarial_loss: 0.0823\n",
      "Epoch 586/1000\n",
      "11/11 [==============================] - 4s 331ms/step - loss: 0.1514 - sparse_categorical_crossentropy: 0.0828 - sparse_categorical_accuracy: 0.9678 - scaled_adversarial_loss: 0.0686 - val_loss: 0.1872 - val_sparse_categorical_crossentropy: 0.1078 - val_sparse_categorical_accuracy: 0.9546 - val_scaled_adversarial_loss: 0.0793\n",
      "Epoch 587/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.1483 - sparse_categorical_crossentropy: 0.0809 - sparse_categorical_accuracy: 0.9727 - scaled_adversarial_loss: 0.0675 - val_loss: 0.1841 - val_sparse_categorical_crossentropy: 0.1108 - val_sparse_categorical_accuracy: 0.9576 - val_scaled_adversarial_loss: 0.0733\n",
      "Epoch 588/1000\n",
      "11/11 [==============================] - 4s 336ms/step - loss: 0.1520 - sparse_categorical_crossentropy: 0.0845 - sparse_categorical_accuracy: 0.9721 - scaled_adversarial_loss: 0.0675 - val_loss: 0.1839 - val_sparse_categorical_crossentropy: 0.1072 - val_sparse_categorical_accuracy: 0.9524 - val_scaled_adversarial_loss: 0.0767\n",
      "Epoch 589/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.1440 - sparse_categorical_crossentropy: 0.0789 - sparse_categorical_accuracy: 0.9721 - scaled_adversarial_loss: 0.0650 - val_loss: 0.1864 - val_sparse_categorical_crossentropy: 0.1057 - val_sparse_categorical_accuracy: 0.9539 - val_scaled_adversarial_loss: 0.0807\n",
      "Epoch 590/1000\n",
      "11/11 [==============================] - 4s 332ms/step - loss: 0.1442 - sparse_categorical_crossentropy: 0.0786 - sparse_categorical_accuracy: 0.9749 - scaled_adversarial_loss: 0.0656 - val_loss: 0.1879 - val_sparse_categorical_crossentropy: 0.1066 - val_sparse_categorical_accuracy: 0.9584 - val_scaled_adversarial_loss: 0.0813\n",
      "Epoch 591/1000\n",
      "11/11 [==============================] - 4s 335ms/step - loss: 0.1386 - sparse_categorical_crossentropy: 0.0733 - sparse_categorical_accuracy: 0.9729 - scaled_adversarial_loss: 0.0652 - val_loss: 0.1999 - val_sparse_categorical_crossentropy: 0.1148 - val_sparse_categorical_accuracy: 0.9561 - val_scaled_adversarial_loss: 0.0850\n",
      "Epoch 592/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.1415 - sparse_categorical_crossentropy: 0.0769 - sparse_categorical_accuracy: 0.9730 - scaled_adversarial_loss: 0.0646 - val_loss: 0.2118 - val_sparse_categorical_crossentropy: 0.1158 - val_sparse_categorical_accuracy: 0.9569 - val_scaled_adversarial_loss: 0.0960\n",
      "Epoch 593/1000\n",
      "11/11 [==============================] - 4s 335ms/step - loss: 0.1523 - sparse_categorical_crossentropy: 0.0830 - sparse_categorical_accuracy: 0.9721 - scaled_adversarial_loss: 0.0692 - val_loss: 0.2112 - val_sparse_categorical_crossentropy: 0.1181 - val_sparse_categorical_accuracy: 0.9569 - val_scaled_adversarial_loss: 0.0931\n",
      "Epoch 594/1000\n",
      "11/11 [==============================] - 4s 335ms/step - loss: 0.1507 - sparse_categorical_crossentropy: 0.0830 - sparse_categorical_accuracy: 0.9702 - scaled_adversarial_loss: 0.0676 - val_loss: 0.2211 - val_sparse_categorical_crossentropy: 0.1296 - val_sparse_categorical_accuracy: 0.9539 - val_scaled_adversarial_loss: 0.0915\n",
      "Epoch 595/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.1465 - sparse_categorical_crossentropy: 0.0796 - sparse_categorical_accuracy: 0.9717 - scaled_adversarial_loss: 0.0669 - val_loss: 0.1881 - val_sparse_categorical_crossentropy: 0.1057 - val_sparse_categorical_accuracy: 0.9576 - val_scaled_adversarial_loss: 0.0824\n",
      "Epoch 596/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.1474 - sparse_categorical_crossentropy: 0.0798 - sparse_categorical_accuracy: 0.9725 - scaled_adversarial_loss: 0.0676 - val_loss: 0.1910 - val_sparse_categorical_crossentropy: 0.1069 - val_sparse_categorical_accuracy: 0.9576 - val_scaled_adversarial_loss: 0.0841\n",
      "Epoch 597/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.1416 - sparse_categorical_crossentropy: 0.0735 - sparse_categorical_accuracy: 0.9734 - scaled_adversarial_loss: 0.0681 - val_loss: 0.1894 - val_sparse_categorical_crossentropy: 0.1066 - val_sparse_categorical_accuracy: 0.9576 - val_scaled_adversarial_loss: 0.0828\n",
      "Epoch 598/1000\n",
      "11/11 [==============================] - 4s 332ms/step - loss: 0.1404 - sparse_categorical_crossentropy: 0.0741 - sparse_categorical_accuracy: 0.9751 - scaled_adversarial_loss: 0.0663 - val_loss: 0.2016 - val_sparse_categorical_crossentropy: 0.1105 - val_sparse_categorical_accuracy: 0.9554 - val_scaled_adversarial_loss: 0.0911\n",
      "Epoch 599/1000\n",
      "11/11 [==============================] - 4s 331ms/step - loss: 0.1492 - sparse_categorical_crossentropy: 0.0812 - sparse_categorical_accuracy: 0.9717 - scaled_adversarial_loss: 0.0679 - val_loss: 0.1924 - val_sparse_categorical_crossentropy: 0.1070 - val_sparse_categorical_accuracy: 0.9591 - val_scaled_adversarial_loss: 0.0854\n",
      "Epoch 600/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.1444 - sparse_categorical_crossentropy: 0.0757 - sparse_categorical_accuracy: 0.9729 - scaled_adversarial_loss: 0.0687 - val_loss: 0.1884 - val_sparse_categorical_crossentropy: 0.1083 - val_sparse_categorical_accuracy: 0.9576 - val_scaled_adversarial_loss: 0.0801\n",
      "Epoch 601/1000\n",
      "11/11 [==============================] - 4s 336ms/step - loss: 0.1503 - sparse_categorical_crossentropy: 0.0804 - sparse_categorical_accuracy: 0.9710 - scaled_adversarial_loss: 0.0699 - val_loss: 0.2095 - val_sparse_categorical_crossentropy: 0.1130 - val_sparse_categorical_accuracy: 0.9569 - val_scaled_adversarial_loss: 0.0965\n",
      "Epoch 602/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.1465 - sparse_categorical_crossentropy: 0.0750 - sparse_categorical_accuracy: 0.9729 - scaled_adversarial_loss: 0.0714 - val_loss: 0.2096 - val_sparse_categorical_crossentropy: 0.1160 - val_sparse_categorical_accuracy: 0.9576 - val_scaled_adversarial_loss: 0.0935\n",
      "Epoch 603/1000\n",
      "11/11 [==============================] - 4s 344ms/step - loss: 0.1421 - sparse_categorical_crossentropy: 0.0740 - sparse_categorical_accuracy: 0.9710 - scaled_adversarial_loss: 0.0681 - val_loss: 0.1910 - val_sparse_categorical_crossentropy: 0.1027 - val_sparse_categorical_accuracy: 0.9576 - val_scaled_adversarial_loss: 0.0882\n",
      "Epoch 604/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.1414 - sparse_categorical_crossentropy: 0.0727 - sparse_categorical_accuracy: 0.9738 - scaled_adversarial_loss: 0.0687 - val_loss: 0.1947 - val_sparse_categorical_crossentropy: 0.1099 - val_sparse_categorical_accuracy: 0.9576 - val_scaled_adversarial_loss: 0.0848\n",
      "Epoch 605/1000\n",
      "11/11 [==============================] - 4s 335ms/step - loss: 0.1371 - sparse_categorical_crossentropy: 0.0721 - sparse_categorical_accuracy: 0.9756 - scaled_adversarial_loss: 0.0649 - val_loss: 0.1938 - val_sparse_categorical_crossentropy: 0.1084 - val_sparse_categorical_accuracy: 0.9576 - val_scaled_adversarial_loss: 0.0854\n",
      "Epoch 606/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.1417 - sparse_categorical_crossentropy: 0.0755 - sparse_categorical_accuracy: 0.9717 - scaled_adversarial_loss: 0.0661 - val_loss: 0.1900 - val_sparse_categorical_crossentropy: 0.1037 - val_sparse_categorical_accuracy: 0.9591 - val_scaled_adversarial_loss: 0.0863\n",
      "Epoch 607/1000\n",
      "11/11 [==============================] - 4s 335ms/step - loss: 0.1448 - sparse_categorical_crossentropy: 0.0763 - sparse_categorical_accuracy: 0.9719 - scaled_adversarial_loss: 0.0684 - val_loss: 0.1762 - val_sparse_categorical_crossentropy: 0.1027 - val_sparse_categorical_accuracy: 0.9584 - val_scaled_adversarial_loss: 0.0734\n",
      "Epoch 608/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.1451 - sparse_categorical_crossentropy: 0.0747 - sparse_categorical_accuracy: 0.9749 - scaled_adversarial_loss: 0.0705 - val_loss: 0.1789 - val_sparse_categorical_crossentropy: 0.1062 - val_sparse_categorical_accuracy: 0.9591 - val_scaled_adversarial_loss: 0.0728\n",
      "Epoch 609/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.1410 - sparse_categorical_crossentropy: 0.0774 - sparse_categorical_accuracy: 0.9743 - scaled_adversarial_loss: 0.0636 - val_loss: 0.1848 - val_sparse_categorical_crossentropy: 0.1100 - val_sparse_categorical_accuracy: 0.9576 - val_scaled_adversarial_loss: 0.0749\n",
      "Epoch 610/1000\n",
      "11/11 [==============================] - 4s 332ms/step - loss: 0.1409 - sparse_categorical_crossentropy: 0.0723 - sparse_categorical_accuracy: 0.9745 - scaled_adversarial_loss: 0.0686 - val_loss: 0.1886 - val_sparse_categorical_crossentropy: 0.1083 - val_sparse_categorical_accuracy: 0.9599 - val_scaled_adversarial_loss: 0.0803\n",
      "Epoch 611/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.1445 - sparse_categorical_crossentropy: 0.0787 - sparse_categorical_accuracy: 0.9712 - scaled_adversarial_loss: 0.0658 - val_loss: 0.2012 - val_sparse_categorical_crossentropy: 0.1110 - val_sparse_categorical_accuracy: 0.9554 - val_scaled_adversarial_loss: 0.0902\n",
      "Epoch 612/1000\n",
      "11/11 [==============================] - 4s 337ms/step - loss: 0.1480 - sparse_categorical_crossentropy: 0.0796 - sparse_categorical_accuracy: 0.9725 - scaled_adversarial_loss: 0.0683 - val_loss: 0.1925 - val_sparse_categorical_crossentropy: 0.1063 - val_sparse_categorical_accuracy: 0.9569 - val_scaled_adversarial_loss: 0.0863\n",
      "Epoch 613/1000\n",
      "11/11 [==============================] - 4s 332ms/step - loss: 0.1419 - sparse_categorical_crossentropy: 0.0772 - sparse_categorical_accuracy: 0.9699 - scaled_adversarial_loss: 0.0648 - val_loss: 0.1877 - val_sparse_categorical_crossentropy: 0.1034 - val_sparse_categorical_accuracy: 0.9606 - val_scaled_adversarial_loss: 0.0843\n",
      "Epoch 614/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.1511 - sparse_categorical_crossentropy: 0.0807 - sparse_categorical_accuracy: 0.9716 - scaled_adversarial_loss: 0.0704 - val_loss: 0.1800 - val_sparse_categorical_crossentropy: 0.1067 - val_sparse_categorical_accuracy: 0.9546 - val_scaled_adversarial_loss: 0.0733\n",
      "Epoch 615/1000\n",
      "11/11 [==============================] - 4s 335ms/step - loss: 0.1419 - sparse_categorical_crossentropy: 0.0775 - sparse_categorical_accuracy: 0.9727 - scaled_adversarial_loss: 0.0644 - val_loss: 0.1903 - val_sparse_categorical_crossentropy: 0.1085 - val_sparse_categorical_accuracy: 0.9591 - val_scaled_adversarial_loss: 0.0818\n",
      "Epoch 616/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.1458 - sparse_categorical_crossentropy: 0.0782 - sparse_categorical_accuracy: 0.9745 - scaled_adversarial_loss: 0.0676 - val_loss: 0.2070 - val_sparse_categorical_crossentropy: 0.1199 - val_sparse_categorical_accuracy: 0.9569 - val_scaled_adversarial_loss: 0.0872\n",
      "Epoch 617/1000\n",
      "11/11 [==============================] - 4s 337ms/step - loss: 0.1489 - sparse_categorical_crossentropy: 0.0842 - sparse_categorical_accuracy: 0.9686 - scaled_adversarial_loss: 0.0647 - val_loss: 0.1834 - val_sparse_categorical_crossentropy: 0.1101 - val_sparse_categorical_accuracy: 0.9606 - val_scaled_adversarial_loss: 0.0734\n",
      "Epoch 618/1000\n",
      "11/11 [==============================] - 4s 337ms/step - loss: 0.1461 - sparse_categorical_crossentropy: 0.0794 - sparse_categorical_accuracy: 0.9723 - scaled_adversarial_loss: 0.0666 - val_loss: 0.1932 - val_sparse_categorical_crossentropy: 0.1052 - val_sparse_categorical_accuracy: 0.9621 - val_scaled_adversarial_loss: 0.0880\n",
      "Epoch 619/1000\n",
      "11/11 [==============================] - 4s 336ms/step - loss: 0.1458 - sparse_categorical_crossentropy: 0.0749 - sparse_categorical_accuracy: 0.9740 - scaled_adversarial_loss: 0.0709 - val_loss: 0.1909 - val_sparse_categorical_crossentropy: 0.1095 - val_sparse_categorical_accuracy: 0.9554 - val_scaled_adversarial_loss: 0.0814\n",
      "Epoch 620/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.1442 - sparse_categorical_crossentropy: 0.0772 - sparse_categorical_accuracy: 0.9708 - scaled_adversarial_loss: 0.0670 - val_loss: 0.1916 - val_sparse_categorical_crossentropy: 0.1115 - val_sparse_categorical_accuracy: 0.9576 - val_scaled_adversarial_loss: 0.0801\n",
      "Epoch 621/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.1407 - sparse_categorical_crossentropy: 0.0761 - sparse_categorical_accuracy: 0.9745 - scaled_adversarial_loss: 0.0647 - val_loss: 0.2169 - val_sparse_categorical_crossentropy: 0.1245 - val_sparse_categorical_accuracy: 0.9584 - val_scaled_adversarial_loss: 0.0924\n",
      "Epoch 622/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.1449 - sparse_categorical_crossentropy: 0.0738 - sparse_categorical_accuracy: 0.9768 - scaled_adversarial_loss: 0.0711 - val_loss: 0.2136 - val_sparse_categorical_crossentropy: 0.1220 - val_sparse_categorical_accuracy: 0.9561 - val_scaled_adversarial_loss: 0.0916\n",
      "Epoch 623/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.1426 - sparse_categorical_crossentropy: 0.0742 - sparse_categorical_accuracy: 0.9755 - scaled_adversarial_loss: 0.0683 - val_loss: 0.1849 - val_sparse_categorical_crossentropy: 0.1082 - val_sparse_categorical_accuracy: 0.9569 - val_scaled_adversarial_loss: 0.0767\n",
      "Epoch 624/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.1477 - sparse_categorical_crossentropy: 0.0800 - sparse_categorical_accuracy: 0.9729 - scaled_adversarial_loss: 0.0677 - val_loss: 0.1891 - val_sparse_categorical_crossentropy: 0.1045 - val_sparse_categorical_accuracy: 0.9546 - val_scaled_adversarial_loss: 0.0846\n",
      "Epoch 625/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.1436 - sparse_categorical_crossentropy: 0.0758 - sparse_categorical_accuracy: 0.9730 - scaled_adversarial_loss: 0.0678 - val_loss: 0.1748 - val_sparse_categorical_crossentropy: 0.1021 - val_sparse_categorical_accuracy: 0.9569 - val_scaled_adversarial_loss: 0.0727\n",
      "Epoch 626/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.1515 - sparse_categorical_crossentropy: 0.0834 - sparse_categorical_accuracy: 0.9717 - scaled_adversarial_loss: 0.0680 - val_loss: 0.1808 - val_sparse_categorical_crossentropy: 0.1048 - val_sparse_categorical_accuracy: 0.9584 - val_scaled_adversarial_loss: 0.0760\n",
      "Epoch 627/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.1447 - sparse_categorical_crossentropy: 0.0773 - sparse_categorical_accuracy: 0.9742 - scaled_adversarial_loss: 0.0674 - val_loss: 0.2009 - val_sparse_categorical_crossentropy: 0.1110 - val_sparse_categorical_accuracy: 0.9554 - val_scaled_adversarial_loss: 0.0899\n",
      "Epoch 628/1000\n",
      "11/11 [==============================] - 4s 339ms/step - loss: 0.1480 - sparse_categorical_crossentropy: 0.0801 - sparse_categorical_accuracy: 0.9725 - scaled_adversarial_loss: 0.0680 - val_loss: 0.1990 - val_sparse_categorical_crossentropy: 0.1138 - val_sparse_categorical_accuracy: 0.9591 - val_scaled_adversarial_loss: 0.0852\n",
      "Epoch 629/1000\n",
      "11/11 [==============================] - 4s 342ms/step - loss: 0.1420 - sparse_categorical_crossentropy: 0.0754 - sparse_categorical_accuracy: 0.9723 - scaled_adversarial_loss: 0.0666 - val_loss: 0.1810 - val_sparse_categorical_crossentropy: 0.1055 - val_sparse_categorical_accuracy: 0.9569 - val_scaled_adversarial_loss: 0.0755\n",
      "Epoch 630/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.1427 - sparse_categorical_crossentropy: 0.0781 - sparse_categorical_accuracy: 0.9717 - scaled_adversarial_loss: 0.0646 - val_loss: 0.1809 - val_sparse_categorical_crossentropy: 0.1024 - val_sparse_categorical_accuracy: 0.9591 - val_scaled_adversarial_loss: 0.0785\n",
      "Epoch 631/1000\n",
      "11/11 [==============================] - 4s 335ms/step - loss: 0.1466 - sparse_categorical_crossentropy: 0.0777 - sparse_categorical_accuracy: 0.9762 - scaled_adversarial_loss: 0.0690 - val_loss: 0.1995 - val_sparse_categorical_crossentropy: 0.1113 - val_sparse_categorical_accuracy: 0.9569 - val_scaled_adversarial_loss: 0.0881\n",
      "Epoch 632/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.1431 - sparse_categorical_crossentropy: 0.0754 - sparse_categorical_accuracy: 0.9723 - scaled_adversarial_loss: 0.0677 - val_loss: 0.1983 - val_sparse_categorical_crossentropy: 0.1125 - val_sparse_categorical_accuracy: 0.9584 - val_scaled_adversarial_loss: 0.0859\n",
      "Epoch 633/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.1330 - sparse_categorical_crossentropy: 0.0645 - sparse_categorical_accuracy: 0.9755 - scaled_adversarial_loss: 0.0685 - val_loss: 0.1873 - val_sparse_categorical_crossentropy: 0.1083 - val_sparse_categorical_accuracy: 0.9569 - val_scaled_adversarial_loss: 0.0790\n",
      "Epoch 634/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.1375 - sparse_categorical_crossentropy: 0.0718 - sparse_categorical_accuracy: 0.9762 - scaled_adversarial_loss: 0.0657 - val_loss: 0.1913 - val_sparse_categorical_crossentropy: 0.1105 - val_sparse_categorical_accuracy: 0.9584 - val_scaled_adversarial_loss: 0.0808\n",
      "Epoch 635/1000\n",
      "11/11 [==============================] - 4s 336ms/step - loss: 0.1404 - sparse_categorical_crossentropy: 0.0773 - sparse_categorical_accuracy: 0.9710 - scaled_adversarial_loss: 0.0631 - val_loss: 0.1818 - val_sparse_categorical_crossentropy: 0.1057 - val_sparse_categorical_accuracy: 0.9576 - val_scaled_adversarial_loss: 0.0761\n",
      "Epoch 636/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.1439 - sparse_categorical_crossentropy: 0.0767 - sparse_categorical_accuracy: 0.9729 - scaled_adversarial_loss: 0.0672 - val_loss: 0.2088 - val_sparse_categorical_crossentropy: 0.1173 - val_sparse_categorical_accuracy: 0.9554 - val_scaled_adversarial_loss: 0.0915\n",
      "Epoch 637/1000\n",
      "11/11 [==============================] - 4s 337ms/step - loss: 0.1416 - sparse_categorical_crossentropy: 0.0720 - sparse_categorical_accuracy: 0.9734 - scaled_adversarial_loss: 0.0696 - val_loss: 0.2028 - val_sparse_categorical_crossentropy: 0.1114 - val_sparse_categorical_accuracy: 0.9569 - val_scaled_adversarial_loss: 0.0914\n",
      "Epoch 638/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.1422 - sparse_categorical_crossentropy: 0.0720 - sparse_categorical_accuracy: 0.9753 - scaled_adversarial_loss: 0.0702 - val_loss: 0.2312 - val_sparse_categorical_crossentropy: 0.1333 - val_sparse_categorical_accuracy: 0.9546 - val_scaled_adversarial_loss: 0.0978\n",
      "Epoch 639/1000\n",
      "11/11 [==============================] - 4s 336ms/step - loss: 0.1411 - sparse_categorical_crossentropy: 0.0732 - sparse_categorical_accuracy: 0.9758 - scaled_adversarial_loss: 0.0679 - val_loss: 0.1902 - val_sparse_categorical_crossentropy: 0.1115 - val_sparse_categorical_accuracy: 0.9569 - val_scaled_adversarial_loss: 0.0787\n",
      "Epoch 640/1000\n",
      "11/11 [==============================] - 4s 336ms/step - loss: 0.1320 - sparse_categorical_crossentropy: 0.0699 - sparse_categorical_accuracy: 0.9762 - scaled_adversarial_loss: 0.0621 - val_loss: 0.2011 - val_sparse_categorical_crossentropy: 0.1194 - val_sparse_categorical_accuracy: 0.9561 - val_scaled_adversarial_loss: 0.0817\n",
      "Epoch 641/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.1385 - sparse_categorical_crossentropy: 0.0703 - sparse_categorical_accuracy: 0.9734 - scaled_adversarial_loss: 0.0682 - val_loss: 0.1970 - val_sparse_categorical_crossentropy: 0.1110 - val_sparse_categorical_accuracy: 0.9584 - val_scaled_adversarial_loss: 0.0860\n",
      "Epoch 642/1000\n",
      "11/11 [==============================] - 4s 332ms/step - loss: 0.1356 - sparse_categorical_crossentropy: 0.0699 - sparse_categorical_accuracy: 0.9749 - scaled_adversarial_loss: 0.0657 - val_loss: 0.2000 - val_sparse_categorical_crossentropy: 0.1092 - val_sparse_categorical_accuracy: 0.9546 - val_scaled_adversarial_loss: 0.0908\n",
      "Epoch 643/1000\n",
      "11/11 [==============================] - 4s 335ms/step - loss: 0.1387 - sparse_categorical_crossentropy: 0.0715 - sparse_categorical_accuracy: 0.9766 - scaled_adversarial_loss: 0.0672 - val_loss: 0.1877 - val_sparse_categorical_crossentropy: 0.1056 - val_sparse_categorical_accuracy: 0.9569 - val_scaled_adversarial_loss: 0.0821\n",
      "Epoch 644/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.1346 - sparse_categorical_crossentropy: 0.0704 - sparse_categorical_accuracy: 0.9769 - scaled_adversarial_loss: 0.0642 - val_loss: 0.1888 - val_sparse_categorical_crossentropy: 0.1073 - val_sparse_categorical_accuracy: 0.9599 - val_scaled_adversarial_loss: 0.0815\n",
      "Epoch 645/1000\n",
      "11/11 [==============================] - 4s 335ms/step - loss: 0.1402 - sparse_categorical_crossentropy: 0.0741 - sparse_categorical_accuracy: 0.9768 - scaled_adversarial_loss: 0.0662 - val_loss: 0.1824 - val_sparse_categorical_crossentropy: 0.1046 - val_sparse_categorical_accuracy: 0.9546 - val_scaled_adversarial_loss: 0.0778\n",
      "Epoch 646/1000\n",
      "11/11 [==============================] - 4s 335ms/step - loss: 0.1401 - sparse_categorical_crossentropy: 0.0725 - sparse_categorical_accuracy: 0.9760 - scaled_adversarial_loss: 0.0676 - val_loss: 0.1885 - val_sparse_categorical_crossentropy: 0.1027 - val_sparse_categorical_accuracy: 0.9591 - val_scaled_adversarial_loss: 0.0858\n",
      "Epoch 647/1000\n",
      "11/11 [==============================] - 4s 335ms/step - loss: 0.1466 - sparse_categorical_crossentropy: 0.0795 - sparse_categorical_accuracy: 0.9710 - scaled_adversarial_loss: 0.0672 - val_loss: 0.1848 - val_sparse_categorical_crossentropy: 0.1092 - val_sparse_categorical_accuracy: 0.9613 - val_scaled_adversarial_loss: 0.0756\n",
      "Epoch 648/1000\n",
      "11/11 [==============================] - 4s 332ms/step - loss: 0.1405 - sparse_categorical_crossentropy: 0.0748 - sparse_categorical_accuracy: 0.9730 - scaled_adversarial_loss: 0.0656 - val_loss: 0.1850 - val_sparse_categorical_crossentropy: 0.1065 - val_sparse_categorical_accuracy: 0.9606 - val_scaled_adversarial_loss: 0.0784\n",
      "Epoch 649/1000\n",
      "11/11 [==============================] - 4s 335ms/step - loss: 0.1420 - sparse_categorical_crossentropy: 0.0745 - sparse_categorical_accuracy: 0.9742 - scaled_adversarial_loss: 0.0675 - val_loss: 0.1869 - val_sparse_categorical_crossentropy: 0.1006 - val_sparse_categorical_accuracy: 0.9576 - val_scaled_adversarial_loss: 0.0862\n",
      "Epoch 650/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.1439 - sparse_categorical_crossentropy: 0.0771 - sparse_categorical_accuracy: 0.9743 - scaled_adversarial_loss: 0.0668 - val_loss: 0.1923 - val_sparse_categorical_crossentropy: 0.1053 - val_sparse_categorical_accuracy: 0.9569 - val_scaled_adversarial_loss: 0.0870\n",
      "Epoch 651/1000\n",
      "11/11 [==============================] - 4s 335ms/step - loss: 0.1443 - sparse_categorical_crossentropy: 0.0755 - sparse_categorical_accuracy: 0.9743 - scaled_adversarial_loss: 0.0687 - val_loss: 0.2033 - val_sparse_categorical_crossentropy: 0.1096 - val_sparse_categorical_accuracy: 0.9569 - val_scaled_adversarial_loss: 0.0938\n",
      "Epoch 652/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.1451 - sparse_categorical_crossentropy: 0.0784 - sparse_categorical_accuracy: 0.9712 - scaled_adversarial_loss: 0.0667 - val_loss: 0.2074 - val_sparse_categorical_crossentropy: 0.1193 - val_sparse_categorical_accuracy: 0.9584 - val_scaled_adversarial_loss: 0.0881\n",
      "Epoch 653/1000\n",
      "11/11 [==============================] - 4s 343ms/step - loss: 0.1382 - sparse_categorical_crossentropy: 0.0714 - sparse_categorical_accuracy: 0.9742 - scaled_adversarial_loss: 0.0669 - val_loss: 0.2014 - val_sparse_categorical_crossentropy: 0.1149 - val_sparse_categorical_accuracy: 0.9584 - val_scaled_adversarial_loss: 0.0865\n",
      "Epoch 654/1000\n",
      "11/11 [==============================] - 4s 337ms/step - loss: 0.1414 - sparse_categorical_crossentropy: 0.0751 - sparse_categorical_accuracy: 0.9756 - scaled_adversarial_loss: 0.0663 - val_loss: 0.1919 - val_sparse_categorical_crossentropy: 0.1055 - val_sparse_categorical_accuracy: 0.9584 - val_scaled_adversarial_loss: 0.0865\n",
      "Epoch 655/1000\n",
      "11/11 [==============================] - 4s 339ms/step - loss: 0.1464 - sparse_categorical_crossentropy: 0.0751 - sparse_categorical_accuracy: 0.9751 - scaled_adversarial_loss: 0.0713 - val_loss: 0.2018 - val_sparse_categorical_crossentropy: 0.1160 - val_sparse_categorical_accuracy: 0.9584 - val_scaled_adversarial_loss: 0.0857\n",
      "Epoch 656/1000\n",
      "11/11 [==============================] - 4s 339ms/step - loss: 0.1401 - sparse_categorical_crossentropy: 0.0739 - sparse_categorical_accuracy: 0.9730 - scaled_adversarial_loss: 0.0662 - val_loss: 0.1970 - val_sparse_categorical_crossentropy: 0.1112 - val_sparse_categorical_accuracy: 0.9606 - val_scaled_adversarial_loss: 0.0857\n",
      "Epoch 657/1000\n",
      "11/11 [==============================] - 4s 329ms/step - loss: 0.1338 - sparse_categorical_crossentropy: 0.0671 - sparse_categorical_accuracy: 0.9747 - scaled_adversarial_loss: 0.0667 - val_loss: 0.1972 - val_sparse_categorical_crossentropy: 0.1101 - val_sparse_categorical_accuracy: 0.9584 - val_scaled_adversarial_loss: 0.0871\n",
      "Epoch 658/1000\n",
      "11/11 [==============================] - 4s 331ms/step - loss: 0.1344 - sparse_categorical_crossentropy: 0.0680 - sparse_categorical_accuracy: 0.9742 - scaled_adversarial_loss: 0.0665 - val_loss: 0.1952 - val_sparse_categorical_crossentropy: 0.1116 - val_sparse_categorical_accuracy: 0.9569 - val_scaled_adversarial_loss: 0.0836\n",
      "Epoch 659/1000\n",
      "11/11 [==============================] - 4s 327ms/step - loss: 0.1312 - sparse_categorical_crossentropy: 0.0668 - sparse_categorical_accuracy: 0.9764 - scaled_adversarial_loss: 0.0644 - val_loss: 0.1883 - val_sparse_categorical_crossentropy: 0.1005 - val_sparse_categorical_accuracy: 0.9584 - val_scaled_adversarial_loss: 0.0879\n",
      "Epoch 660/1000\n",
      "11/11 [==============================] - 4s 327ms/step - loss: 0.1360 - sparse_categorical_crossentropy: 0.0713 - sparse_categorical_accuracy: 0.9740 - scaled_adversarial_loss: 0.0648 - val_loss: 0.1913 - val_sparse_categorical_crossentropy: 0.1064 - val_sparse_categorical_accuracy: 0.9599 - val_scaled_adversarial_loss: 0.0849\n",
      "Epoch 661/1000\n",
      "11/11 [==============================] - 4s 329ms/step - loss: 0.1409 - sparse_categorical_crossentropy: 0.0706 - sparse_categorical_accuracy: 0.9766 - scaled_adversarial_loss: 0.0703 - val_loss: 0.1972 - val_sparse_categorical_crossentropy: 0.1124 - val_sparse_categorical_accuracy: 0.9584 - val_scaled_adversarial_loss: 0.0849\n",
      "Epoch 662/1000\n",
      "11/11 [==============================] - 4s 329ms/step - loss: 0.1373 - sparse_categorical_crossentropy: 0.0701 - sparse_categorical_accuracy: 0.9769 - scaled_adversarial_loss: 0.0672 - val_loss: 0.1757 - val_sparse_categorical_crossentropy: 0.1048 - val_sparse_categorical_accuracy: 0.9569 - val_scaled_adversarial_loss: 0.0709\n",
      "Epoch 663/1000\n",
      "11/11 [==============================] - 4s 330ms/step - loss: 0.1376 - sparse_categorical_crossentropy: 0.0728 - sparse_categorical_accuracy: 0.9751 - scaled_adversarial_loss: 0.0647 - val_loss: 0.1895 - val_sparse_categorical_crossentropy: 0.1065 - val_sparse_categorical_accuracy: 0.9561 - val_scaled_adversarial_loss: 0.0830\n",
      "Epoch 664/1000\n",
      "11/11 [==============================] - 4s 326ms/step - loss: 0.1393 - sparse_categorical_crossentropy: 0.0705 - sparse_categorical_accuracy: 0.9773 - scaled_adversarial_loss: 0.0688 - val_loss: 0.1963 - val_sparse_categorical_crossentropy: 0.1145 - val_sparse_categorical_accuracy: 0.9576 - val_scaled_adversarial_loss: 0.0818\n",
      "Epoch 665/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.1331 - sparse_categorical_crossentropy: 0.0710 - sparse_categorical_accuracy: 0.9753 - scaled_adversarial_loss: 0.0621 - val_loss: 0.2011 - val_sparse_categorical_crossentropy: 0.1099 - val_sparse_categorical_accuracy: 0.9613 - val_scaled_adversarial_loss: 0.0913\n",
      "Epoch 666/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.1350 - sparse_categorical_crossentropy: 0.0706 - sparse_categorical_accuracy: 0.9751 - scaled_adversarial_loss: 0.0644 - val_loss: 0.1934 - val_sparse_categorical_crossentropy: 0.1063 - val_sparse_categorical_accuracy: 0.9599 - val_scaled_adversarial_loss: 0.0871\n",
      "Epoch 667/1000\n",
      "11/11 [==============================] - 4s 332ms/step - loss: 0.1311 - sparse_categorical_crossentropy: 0.0664 - sparse_categorical_accuracy: 0.9766 - scaled_adversarial_loss: 0.0647 - val_loss: 0.1783 - val_sparse_categorical_crossentropy: 0.0955 - val_sparse_categorical_accuracy: 0.9599 - val_scaled_adversarial_loss: 0.0828\n",
      "Epoch 668/1000\n",
      "11/11 [==============================] - 4s 331ms/step - loss: 0.1439 - sparse_categorical_crossentropy: 0.0732 - sparse_categorical_accuracy: 0.9747 - scaled_adversarial_loss: 0.0707 - val_loss: 0.1946 - val_sparse_categorical_crossentropy: 0.1108 - val_sparse_categorical_accuracy: 0.9576 - val_scaled_adversarial_loss: 0.0838\n",
      "Epoch 669/1000\n",
      "11/11 [==============================] - 4s 329ms/step - loss: 0.1370 - sparse_categorical_crossentropy: 0.0725 - sparse_categorical_accuracy: 0.9760 - scaled_adversarial_loss: 0.0645 - val_loss: 0.1902 - val_sparse_categorical_crossentropy: 0.1058 - val_sparse_categorical_accuracy: 0.9606 - val_scaled_adversarial_loss: 0.0845\n",
      "Epoch 670/1000\n",
      "11/11 [==============================] - 4s 328ms/step - loss: 0.1418 - sparse_categorical_crossentropy: 0.0798 - sparse_categorical_accuracy: 0.9714 - scaled_adversarial_loss: 0.0620 - val_loss: 0.1717 - val_sparse_categorical_crossentropy: 0.1014 - val_sparse_categorical_accuracy: 0.9606 - val_scaled_adversarial_loss: 0.0703\n",
      "Epoch 671/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.1338 - sparse_categorical_crossentropy: 0.0682 - sparse_categorical_accuracy: 0.9762 - scaled_adversarial_loss: 0.0656 - val_loss: 0.1830 - val_sparse_categorical_crossentropy: 0.1042 - val_sparse_categorical_accuracy: 0.9584 - val_scaled_adversarial_loss: 0.0788\n",
      "Epoch 672/1000\n",
      "11/11 [==============================] - 4s 327ms/step - loss: 0.1328 - sparse_categorical_crossentropy: 0.0689 - sparse_categorical_accuracy: 0.9766 - scaled_adversarial_loss: 0.0639 - val_loss: 0.1858 - val_sparse_categorical_crossentropy: 0.1061 - val_sparse_categorical_accuracy: 0.9576 - val_scaled_adversarial_loss: 0.0797\n",
      "Epoch 673/1000\n",
      "11/11 [==============================] - 4s 328ms/step - loss: 0.1397 - sparse_categorical_crossentropy: 0.0716 - sparse_categorical_accuracy: 0.9756 - scaled_adversarial_loss: 0.0682 - val_loss: 0.1813 - val_sparse_categorical_crossentropy: 0.1021 - val_sparse_categorical_accuracy: 0.9576 - val_scaled_adversarial_loss: 0.0792\n",
      "Epoch 674/1000\n",
      "11/11 [==============================] - 4s 327ms/step - loss: 0.1374 - sparse_categorical_crossentropy: 0.0711 - sparse_categorical_accuracy: 0.9764 - scaled_adversarial_loss: 0.0663 - val_loss: 0.1974 - val_sparse_categorical_crossentropy: 0.1090 - val_sparse_categorical_accuracy: 0.9599 - val_scaled_adversarial_loss: 0.0885\n",
      "Epoch 675/1000\n",
      "11/11 [==============================] - 4s 325ms/step - loss: 0.1374 - sparse_categorical_crossentropy: 0.0708 - sparse_categorical_accuracy: 0.9751 - scaled_adversarial_loss: 0.0666 - val_loss: 0.1913 - val_sparse_categorical_crossentropy: 0.1077 - val_sparse_categorical_accuracy: 0.9613 - val_scaled_adversarial_loss: 0.0836\n",
      "Epoch 676/1000\n",
      "11/11 [==============================] - 4s 325ms/step - loss: 0.1329 - sparse_categorical_crossentropy: 0.0681 - sparse_categorical_accuracy: 0.9779 - scaled_adversarial_loss: 0.0649 - val_loss: 0.1773 - val_sparse_categorical_crossentropy: 0.1006 - val_sparse_categorical_accuracy: 0.9599 - val_scaled_adversarial_loss: 0.0767\n",
      "Epoch 677/1000\n",
      "11/11 [==============================] - 4s 338ms/step - loss: 0.1435 - sparse_categorical_crossentropy: 0.0764 - sparse_categorical_accuracy: 0.9756 - scaled_adversarial_loss: 0.0671 - val_loss: 0.1770 - val_sparse_categorical_crossentropy: 0.0988 - val_sparse_categorical_accuracy: 0.9613 - val_scaled_adversarial_loss: 0.0782\n",
      "Epoch 678/1000\n",
      "11/11 [==============================] - 4s 325ms/step - loss: 0.1379 - sparse_categorical_crossentropy: 0.0713 - sparse_categorical_accuracy: 0.9751 - scaled_adversarial_loss: 0.0666 - val_loss: 0.1774 - val_sparse_categorical_crossentropy: 0.1059 - val_sparse_categorical_accuracy: 0.9561 - val_scaled_adversarial_loss: 0.0715\n",
      "Epoch 679/1000\n",
      "11/11 [==============================] - 4s 328ms/step - loss: 0.1428 - sparse_categorical_crossentropy: 0.0777 - sparse_categorical_accuracy: 0.9721 - scaled_adversarial_loss: 0.0651 - val_loss: 0.1796 - val_sparse_categorical_crossentropy: 0.1045 - val_sparse_categorical_accuracy: 0.9561 - val_scaled_adversarial_loss: 0.0750\n",
      "Epoch 680/1000\n",
      "11/11 [==============================] - 4s 327ms/step - loss: 0.1365 - sparse_categorical_crossentropy: 0.0704 - sparse_categorical_accuracy: 0.9749 - scaled_adversarial_loss: 0.0661 - val_loss: 0.1958 - val_sparse_categorical_crossentropy: 0.1073 - val_sparse_categorical_accuracy: 0.9561 - val_scaled_adversarial_loss: 0.0885\n",
      "Epoch 681/1000\n",
      "11/11 [==============================] - 4s 326ms/step - loss: 0.1405 - sparse_categorical_crossentropy: 0.0729 - sparse_categorical_accuracy: 0.9727 - scaled_adversarial_loss: 0.0676 - val_loss: 0.1960 - val_sparse_categorical_crossentropy: 0.1062 - val_sparse_categorical_accuracy: 0.9554 - val_scaled_adversarial_loss: 0.0898\n",
      "Epoch 682/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.1342 - sparse_categorical_crossentropy: 0.0707 - sparse_categorical_accuracy: 0.9749 - scaled_adversarial_loss: 0.0634 - val_loss: 0.1951 - val_sparse_categorical_crossentropy: 0.1150 - val_sparse_categorical_accuracy: 0.9554 - val_scaled_adversarial_loss: 0.0801\n",
      "Epoch 683/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.1421 - sparse_categorical_crossentropy: 0.0751 - sparse_categorical_accuracy: 0.9743 - scaled_adversarial_loss: 0.0670 - val_loss: 0.1974 - val_sparse_categorical_crossentropy: 0.1085 - val_sparse_categorical_accuracy: 0.9576 - val_scaled_adversarial_loss: 0.0889\n",
      "Epoch 684/1000\n",
      "11/11 [==============================] - 4s 330ms/step - loss: 0.1360 - sparse_categorical_crossentropy: 0.0706 - sparse_categorical_accuracy: 0.9758 - scaled_adversarial_loss: 0.0654 - val_loss: 0.1780 - val_sparse_categorical_crossentropy: 0.0985 - val_sparse_categorical_accuracy: 0.9591 - val_scaled_adversarial_loss: 0.0794\n",
      "Epoch 685/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.1387 - sparse_categorical_crossentropy: 0.0742 - sparse_categorical_accuracy: 0.9740 - scaled_adversarial_loss: 0.0645 - val_loss: 0.1994 - val_sparse_categorical_crossentropy: 0.1117 - val_sparse_categorical_accuracy: 0.9613 - val_scaled_adversarial_loss: 0.0877\n",
      "Epoch 686/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.1406 - sparse_categorical_crossentropy: 0.0739 - sparse_categorical_accuracy: 0.9749 - scaled_adversarial_loss: 0.0667 - val_loss: 0.1864 - val_sparse_categorical_crossentropy: 0.1023 - val_sparse_categorical_accuracy: 0.9599 - val_scaled_adversarial_loss: 0.0841\n",
      "Epoch 687/1000\n",
      "11/11 [==============================] - 4s 332ms/step - loss: 0.1345 - sparse_categorical_crossentropy: 0.0716 - sparse_categorical_accuracy: 0.9760 - scaled_adversarial_loss: 0.0629 - val_loss: 0.1878 - val_sparse_categorical_crossentropy: 0.1078 - val_sparse_categorical_accuracy: 0.9569 - val_scaled_adversarial_loss: 0.0800\n",
      "Epoch 688/1000\n",
      "11/11 [==============================] - 4s 330ms/step - loss: 0.1369 - sparse_categorical_crossentropy: 0.0701 - sparse_categorical_accuracy: 0.9747 - scaled_adversarial_loss: 0.0668 - val_loss: 0.2127 - val_sparse_categorical_crossentropy: 0.1100 - val_sparse_categorical_accuracy: 0.9584 - val_scaled_adversarial_loss: 0.1027\n",
      "Epoch 689/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.1384 - sparse_categorical_crossentropy: 0.0686 - sparse_categorical_accuracy: 0.9762 - scaled_adversarial_loss: 0.0698 - val_loss: 0.2030 - val_sparse_categorical_crossentropy: 0.1120 - val_sparse_categorical_accuracy: 0.9584 - val_scaled_adversarial_loss: 0.0910\n",
      "Epoch 690/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.1396 - sparse_categorical_crossentropy: 0.0715 - sparse_categorical_accuracy: 0.9734 - scaled_adversarial_loss: 0.0680 - val_loss: 0.1916 - val_sparse_categorical_crossentropy: 0.1121 - val_sparse_categorical_accuracy: 0.9606 - val_scaled_adversarial_loss: 0.0795\n",
      "Epoch 691/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.1426 - sparse_categorical_crossentropy: 0.0765 - sparse_categorical_accuracy: 0.9755 - scaled_adversarial_loss: 0.0661 - val_loss: 0.1945 - val_sparse_categorical_crossentropy: 0.1122 - val_sparse_categorical_accuracy: 0.9554 - val_scaled_adversarial_loss: 0.0823\n",
      "Epoch 692/1000\n",
      "11/11 [==============================] - 4s 331ms/step - loss: 0.1416 - sparse_categorical_crossentropy: 0.0737 - sparse_categorical_accuracy: 0.9736 - scaled_adversarial_loss: 0.0679 - val_loss: 0.1928 - val_sparse_categorical_crossentropy: 0.1073 - val_sparse_categorical_accuracy: 0.9606 - val_scaled_adversarial_loss: 0.0855\n",
      "Epoch 693/1000\n",
      "11/11 [==============================] - 4s 332ms/step - loss: 0.1364 - sparse_categorical_crossentropy: 0.0700 - sparse_categorical_accuracy: 0.9760 - scaled_adversarial_loss: 0.0664 - val_loss: 0.1864 - val_sparse_categorical_crossentropy: 0.1040 - val_sparse_categorical_accuracy: 0.9591 - val_scaled_adversarial_loss: 0.0824\n",
      "Epoch 694/1000\n",
      "11/11 [==============================] - 4s 331ms/step - loss: 0.1386 - sparse_categorical_crossentropy: 0.0718 - sparse_categorical_accuracy: 0.9773 - scaled_adversarial_loss: 0.0668 - val_loss: 0.2073 - val_sparse_categorical_crossentropy: 0.1143 - val_sparse_categorical_accuracy: 0.9569 - val_scaled_adversarial_loss: 0.0930\n",
      "Epoch 695/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.1357 - sparse_categorical_crossentropy: 0.0700 - sparse_categorical_accuracy: 0.9760 - scaled_adversarial_loss: 0.0657 - val_loss: 0.2001 - val_sparse_categorical_crossentropy: 0.1181 - val_sparse_categorical_accuracy: 0.9606 - val_scaled_adversarial_loss: 0.0820\n",
      "Epoch 696/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.1336 - sparse_categorical_crossentropy: 0.0672 - sparse_categorical_accuracy: 0.9794 - scaled_adversarial_loss: 0.0664 - val_loss: 0.2026 - val_sparse_categorical_crossentropy: 0.1085 - val_sparse_categorical_accuracy: 0.9569 - val_scaled_adversarial_loss: 0.0941\n",
      "Epoch 697/1000\n",
      "11/11 [==============================] - 4s 330ms/step - loss: 0.1382 - sparse_categorical_crossentropy: 0.0714 - sparse_categorical_accuracy: 0.9740 - scaled_adversarial_loss: 0.0668 - val_loss: 0.1960 - val_sparse_categorical_crossentropy: 0.1129 - val_sparse_categorical_accuracy: 0.9561 - val_scaled_adversarial_loss: 0.0830\n",
      "Epoch 698/1000\n",
      "11/11 [==============================] - 4s 332ms/step - loss: 0.1369 - sparse_categorical_crossentropy: 0.0724 - sparse_categorical_accuracy: 0.9740 - scaled_adversarial_loss: 0.0646 - val_loss: 0.1959 - val_sparse_categorical_crossentropy: 0.1098 - val_sparse_categorical_accuracy: 0.9561 - val_scaled_adversarial_loss: 0.0861\n",
      "Epoch 699/1000\n",
      "11/11 [==============================] - 4s 329ms/step - loss: 0.1343 - sparse_categorical_crossentropy: 0.0685 - sparse_categorical_accuracy: 0.9768 - scaled_adversarial_loss: 0.0658 - val_loss: 0.1753 - val_sparse_categorical_crossentropy: 0.0981 - val_sparse_categorical_accuracy: 0.9613 - val_scaled_adversarial_loss: 0.0772\n",
      "Epoch 700/1000\n",
      "11/11 [==============================] - 4s 336ms/step - loss: 0.1310 - sparse_categorical_crossentropy: 0.0673 - sparse_categorical_accuracy: 0.9760 - scaled_adversarial_loss: 0.0636 - val_loss: 0.2010 - val_sparse_categorical_crossentropy: 0.1075 - val_sparse_categorical_accuracy: 0.9599 - val_scaled_adversarial_loss: 0.0935\n",
      "Epoch 701/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.1288 - sparse_categorical_crossentropy: 0.0624 - sparse_categorical_accuracy: 0.9786 - scaled_adversarial_loss: 0.0664 - val_loss: 0.2054 - val_sparse_categorical_crossentropy: 0.1125 - val_sparse_categorical_accuracy: 0.9546 - val_scaled_adversarial_loss: 0.0929\n",
      "Epoch 702/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.1345 - sparse_categorical_crossentropy: 0.0683 - sparse_categorical_accuracy: 0.9779 - scaled_adversarial_loss: 0.0662 - val_loss: 0.1876 - val_sparse_categorical_crossentropy: 0.0986 - val_sparse_categorical_accuracy: 0.9561 - val_scaled_adversarial_loss: 0.0890\n",
      "Epoch 703/1000\n",
      "11/11 [==============================] - 4s 332ms/step - loss: 0.1419 - sparse_categorical_crossentropy: 0.0762 - sparse_categorical_accuracy: 0.9723 - scaled_adversarial_loss: 0.0657 - val_loss: 0.1840 - val_sparse_categorical_crossentropy: 0.1072 - val_sparse_categorical_accuracy: 0.9576 - val_scaled_adversarial_loss: 0.0768\n",
      "Epoch 704/1000\n",
      "11/11 [==============================] - 4s 332ms/step - loss: 0.1333 - sparse_categorical_crossentropy: 0.0717 - sparse_categorical_accuracy: 0.9747 - scaled_adversarial_loss: 0.0617 - val_loss: 0.1988 - val_sparse_categorical_crossentropy: 0.1041 - val_sparse_categorical_accuracy: 0.9584 - val_scaled_adversarial_loss: 0.0946\n",
      "Epoch 705/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.1427 - sparse_categorical_crossentropy: 0.0771 - sparse_categorical_accuracy: 0.9699 - scaled_adversarial_loss: 0.0656 - val_loss: 0.2028 - val_sparse_categorical_crossentropy: 0.1071 - val_sparse_categorical_accuracy: 0.9584 - val_scaled_adversarial_loss: 0.0956\n",
      "Epoch 706/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.1454 - sparse_categorical_crossentropy: 0.0754 - sparse_categorical_accuracy: 0.9734 - scaled_adversarial_loss: 0.0699 - val_loss: 0.1939 - val_sparse_categorical_crossentropy: 0.1075 - val_sparse_categorical_accuracy: 0.9591 - val_scaled_adversarial_loss: 0.0864\n",
      "Epoch 707/1000\n",
      "11/11 [==============================] - 4s 332ms/step - loss: 0.1322 - sparse_categorical_crossentropy: 0.0658 - sparse_categorical_accuracy: 0.9775 - scaled_adversarial_loss: 0.0664 - val_loss: 0.2020 - val_sparse_categorical_crossentropy: 0.1099 - val_sparse_categorical_accuracy: 0.9599 - val_scaled_adversarial_loss: 0.0921\n",
      "Epoch 708/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.1339 - sparse_categorical_crossentropy: 0.0689 - sparse_categorical_accuracy: 0.9764 - scaled_adversarial_loss: 0.0650 - val_loss: 0.1867 - val_sparse_categorical_crossentropy: 0.1047 - val_sparse_categorical_accuracy: 0.9569 - val_scaled_adversarial_loss: 0.0821\n",
      "Epoch 709/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.1356 - sparse_categorical_crossentropy: 0.0715 - sparse_categorical_accuracy: 0.9749 - scaled_adversarial_loss: 0.0641 - val_loss: 0.1898 - val_sparse_categorical_crossentropy: 0.1056 - val_sparse_categorical_accuracy: 0.9584 - val_scaled_adversarial_loss: 0.0843\n",
      "Epoch 710/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.1279 - sparse_categorical_crossentropy: 0.0624 - sparse_categorical_accuracy: 0.9775 - scaled_adversarial_loss: 0.0655 - val_loss: 0.1828 - val_sparse_categorical_crossentropy: 0.1031 - val_sparse_categorical_accuracy: 0.9584 - val_scaled_adversarial_loss: 0.0797\n",
      "Epoch 711/1000\n",
      "11/11 [==============================] - 4s 332ms/step - loss: 0.1281 - sparse_categorical_crossentropy: 0.0671 - sparse_categorical_accuracy: 0.9762 - scaled_adversarial_loss: 0.0610 - val_loss: 0.1955 - val_sparse_categorical_crossentropy: 0.1108 - val_sparse_categorical_accuracy: 0.9584 - val_scaled_adversarial_loss: 0.0847\n",
      "Epoch 712/1000\n",
      "11/11 [==============================] - 4s 332ms/step - loss: 0.1351 - sparse_categorical_crossentropy: 0.0696 - sparse_categorical_accuracy: 0.9756 - scaled_adversarial_loss: 0.0655 - val_loss: 0.1927 - val_sparse_categorical_crossentropy: 0.1086 - val_sparse_categorical_accuracy: 0.9584 - val_scaled_adversarial_loss: 0.0841\n",
      "Epoch 713/1000\n",
      "11/11 [==============================] - 4s 331ms/step - loss: 0.1407 - sparse_categorical_crossentropy: 0.0767 - sparse_categorical_accuracy: 0.9732 - scaled_adversarial_loss: 0.0640 - val_loss: 0.1995 - val_sparse_categorical_crossentropy: 0.1097 - val_sparse_categorical_accuracy: 0.9584 - val_scaled_adversarial_loss: 0.0898\n",
      "Epoch 714/1000\n",
      "11/11 [==============================] - 4s 331ms/step - loss: 0.1318 - sparse_categorical_crossentropy: 0.0680 - sparse_categorical_accuracy: 0.9775 - scaled_adversarial_loss: 0.0638 - val_loss: 0.1951 - val_sparse_categorical_crossentropy: 0.1055 - val_sparse_categorical_accuracy: 0.9613 - val_scaled_adversarial_loss: 0.0897\n",
      "Epoch 715/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.1327 - sparse_categorical_crossentropy: 0.0680 - sparse_categorical_accuracy: 0.9764 - scaled_adversarial_loss: 0.0646 - val_loss: 0.2049 - val_sparse_categorical_crossentropy: 0.1113 - val_sparse_categorical_accuracy: 0.9584 - val_scaled_adversarial_loss: 0.0936\n",
      "Epoch 716/1000\n",
      "11/11 [==============================] - 4s 329ms/step - loss: 0.1367 - sparse_categorical_crossentropy: 0.0676 - sparse_categorical_accuracy: 0.9762 - scaled_adversarial_loss: 0.0692 - val_loss: 0.1884 - val_sparse_categorical_crossentropy: 0.1045 - val_sparse_categorical_accuracy: 0.9591 - val_scaled_adversarial_loss: 0.0838\n",
      "Epoch 717/1000\n",
      "11/11 [==============================] - 4s 332ms/step - loss: 0.1395 - sparse_categorical_crossentropy: 0.0768 - sparse_categorical_accuracy: 0.9736 - scaled_adversarial_loss: 0.0627 - val_loss: 0.2026 - val_sparse_categorical_crossentropy: 0.1104 - val_sparse_categorical_accuracy: 0.9576 - val_scaled_adversarial_loss: 0.0923\n",
      "Epoch 718/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.1401 - sparse_categorical_crossentropy: 0.0736 - sparse_categorical_accuracy: 0.9747 - scaled_adversarial_loss: 0.0665 - val_loss: 0.1912 - val_sparse_categorical_crossentropy: 0.1085 - val_sparse_categorical_accuracy: 0.9613 - val_scaled_adversarial_loss: 0.0826\n",
      "Epoch 719/1000\n",
      "11/11 [==============================] - 4s 332ms/step - loss: 0.1374 - sparse_categorical_crossentropy: 0.0728 - sparse_categorical_accuracy: 0.9730 - scaled_adversarial_loss: 0.0646 - val_loss: 0.2159 - val_sparse_categorical_crossentropy: 0.1170 - val_sparse_categorical_accuracy: 0.9591 - val_scaled_adversarial_loss: 0.0989\n",
      "Epoch 720/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.1444 - sparse_categorical_crossentropy: 0.0758 - sparse_categorical_accuracy: 0.9725 - scaled_adversarial_loss: 0.0686 - val_loss: 0.1875 - val_sparse_categorical_crossentropy: 0.1051 - val_sparse_categorical_accuracy: 0.9584 - val_scaled_adversarial_loss: 0.0824\n",
      "Epoch 721/1000\n",
      "11/11 [==============================] - 4s 330ms/step - loss: 0.1436 - sparse_categorical_crossentropy: 0.0774 - sparse_categorical_accuracy: 0.9732 - scaled_adversarial_loss: 0.0663 - val_loss: 0.1743 - val_sparse_categorical_crossentropy: 0.0999 - val_sparse_categorical_accuracy: 0.9576 - val_scaled_adversarial_loss: 0.0744\n",
      "Epoch 722/1000\n",
      "11/11 [==============================] - 4s 331ms/step - loss: 0.1379 - sparse_categorical_crossentropy: 0.0732 - sparse_categorical_accuracy: 0.9729 - scaled_adversarial_loss: 0.0646 - val_loss: 0.1798 - val_sparse_categorical_crossentropy: 0.1030 - val_sparse_categorical_accuracy: 0.9576 - val_scaled_adversarial_loss: 0.0768\n",
      "Epoch 723/1000\n",
      "11/11 [==============================] - 4s 342ms/step - loss: 0.1310 - sparse_categorical_crossentropy: 0.0652 - sparse_categorical_accuracy: 0.9799 - scaled_adversarial_loss: 0.0659 - val_loss: 0.1798 - val_sparse_categorical_crossentropy: 0.1003 - val_sparse_categorical_accuracy: 0.9584 - val_scaled_adversarial_loss: 0.0795\n",
      "Epoch 724/1000\n",
      "11/11 [==============================] - 4s 337ms/step - loss: 0.1292 - sparse_categorical_crossentropy: 0.0648 - sparse_categorical_accuracy: 0.9771 - scaled_adversarial_loss: 0.0644 - val_loss: 0.1920 - val_sparse_categorical_crossentropy: 0.1090 - val_sparse_categorical_accuracy: 0.9554 - val_scaled_adversarial_loss: 0.0830\n",
      "Epoch 725/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.1324 - sparse_categorical_crossentropy: 0.0658 - sparse_categorical_accuracy: 0.9775 - scaled_adversarial_loss: 0.0666 - val_loss: 0.1755 - val_sparse_categorical_crossentropy: 0.0969 - val_sparse_categorical_accuracy: 0.9584 - val_scaled_adversarial_loss: 0.0786\n",
      "Epoch 726/1000\n",
      "11/11 [==============================] - 4s 336ms/step - loss: 0.1366 - sparse_categorical_crossentropy: 0.0708 - sparse_categorical_accuracy: 0.9773 - scaled_adversarial_loss: 0.0658 - val_loss: 0.1894 - val_sparse_categorical_crossentropy: 0.1088 - val_sparse_categorical_accuracy: 0.9539 - val_scaled_adversarial_loss: 0.0806\n",
      "Epoch 727/1000\n",
      "11/11 [==============================] - 4s 339ms/step - loss: 0.1393 - sparse_categorical_crossentropy: 0.0725 - sparse_categorical_accuracy: 0.9755 - scaled_adversarial_loss: 0.0668 - val_loss: 0.1770 - val_sparse_categorical_crossentropy: 0.1012 - val_sparse_categorical_accuracy: 0.9584 - val_scaled_adversarial_loss: 0.0758\n",
      "Epoch 728/1000\n",
      "11/11 [==============================] - 4s 335ms/step - loss: 0.1307 - sparse_categorical_crossentropy: 0.0672 - sparse_categorical_accuracy: 0.9773 - scaled_adversarial_loss: 0.0635 - val_loss: 0.1818 - val_sparse_categorical_crossentropy: 0.1034 - val_sparse_categorical_accuracy: 0.9606 - val_scaled_adversarial_loss: 0.0784\n",
      "Epoch 729/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.1255 - sparse_categorical_crossentropy: 0.0622 - sparse_categorical_accuracy: 0.9795 - scaled_adversarial_loss: 0.0633 - val_loss: 0.1853 - val_sparse_categorical_crossentropy: 0.1003 - val_sparse_categorical_accuracy: 0.9591 - val_scaled_adversarial_loss: 0.0851\n",
      "Epoch 730/1000\n",
      "11/11 [==============================] - 4s 332ms/step - loss: 0.1316 - sparse_categorical_crossentropy: 0.0670 - sparse_categorical_accuracy: 0.9760 - scaled_adversarial_loss: 0.0646 - val_loss: 0.1826 - val_sparse_categorical_crossentropy: 0.1061 - val_sparse_categorical_accuracy: 0.9576 - val_scaled_adversarial_loss: 0.0765\n",
      "Epoch 731/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.1364 - sparse_categorical_crossentropy: 0.0717 - sparse_categorical_accuracy: 0.9764 - scaled_adversarial_loss: 0.0647 - val_loss: 0.1694 - val_sparse_categorical_crossentropy: 0.1027 - val_sparse_categorical_accuracy: 0.9606 - val_scaled_adversarial_loss: 0.0667\n",
      "Epoch 732/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.1378 - sparse_categorical_crossentropy: 0.0720 - sparse_categorical_accuracy: 0.9773 - scaled_adversarial_loss: 0.0658 - val_loss: 0.1889 - val_sparse_categorical_crossentropy: 0.1090 - val_sparse_categorical_accuracy: 0.9554 - val_scaled_adversarial_loss: 0.0799\n",
      "Epoch 733/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.1454 - sparse_categorical_crossentropy: 0.0816 - sparse_categorical_accuracy: 0.9736 - scaled_adversarial_loss: 0.0639 - val_loss: 0.1863 - val_sparse_categorical_crossentropy: 0.1113 - val_sparse_categorical_accuracy: 0.9561 - val_scaled_adversarial_loss: 0.0750\n",
      "Epoch 734/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.1379 - sparse_categorical_crossentropy: 0.0713 - sparse_categorical_accuracy: 0.9756 - scaled_adversarial_loss: 0.0666 - val_loss: 0.2007 - val_sparse_categorical_crossentropy: 0.1167 - val_sparse_categorical_accuracy: 0.9561 - val_scaled_adversarial_loss: 0.0840\n",
      "Epoch 735/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.1402 - sparse_categorical_crossentropy: 0.0747 - sparse_categorical_accuracy: 0.9725 - scaled_adversarial_loss: 0.0655 - val_loss: 0.1818 - val_sparse_categorical_crossentropy: 0.1021 - val_sparse_categorical_accuracy: 0.9591 - val_scaled_adversarial_loss: 0.0798\n",
      "Epoch 736/1000\n",
      "11/11 [==============================] - 4s 331ms/step - loss: 0.1281 - sparse_categorical_crossentropy: 0.0627 - sparse_categorical_accuracy: 0.9786 - scaled_adversarial_loss: 0.0654 - val_loss: 0.1893 - val_sparse_categorical_crossentropy: 0.1066 - val_sparse_categorical_accuracy: 0.9569 - val_scaled_adversarial_loss: 0.0827\n",
      "Epoch 737/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.1299 - sparse_categorical_crossentropy: 0.0668 - sparse_categorical_accuracy: 0.9768 - scaled_adversarial_loss: 0.0631 - val_loss: 0.1911 - val_sparse_categorical_crossentropy: 0.1115 - val_sparse_categorical_accuracy: 0.9584 - val_scaled_adversarial_loss: 0.0796\n",
      "Epoch 738/1000\n",
      "11/11 [==============================] - 4s 330ms/step - loss: 0.1344 - sparse_categorical_crossentropy: 0.0716 - sparse_categorical_accuracy: 0.9753 - scaled_adversarial_loss: 0.0628 - val_loss: 0.1821 - val_sparse_categorical_crossentropy: 0.1027 - val_sparse_categorical_accuracy: 0.9591 - val_scaled_adversarial_loss: 0.0794\n",
      "Epoch 739/1000\n",
      "11/11 [==============================] - 4s 332ms/step - loss: 0.1275 - sparse_categorical_crossentropy: 0.0629 - sparse_categorical_accuracy: 0.9792 - scaled_adversarial_loss: 0.0646 - val_loss: 0.2005 - val_sparse_categorical_crossentropy: 0.1107 - val_sparse_categorical_accuracy: 0.9584 - val_scaled_adversarial_loss: 0.0899\n",
      "Epoch 740/1000\n",
      "11/11 [==============================] - 4s 332ms/step - loss: 0.1339 - sparse_categorical_crossentropy: 0.0709 - sparse_categorical_accuracy: 0.9762 - scaled_adversarial_loss: 0.0630 - val_loss: 0.1860 - val_sparse_categorical_crossentropy: 0.1080 - val_sparse_categorical_accuracy: 0.9584 - val_scaled_adversarial_loss: 0.0780\n",
      "Epoch 741/1000\n",
      "11/11 [==============================] - 4s 335ms/step - loss: 0.1316 - sparse_categorical_crossentropy: 0.0687 - sparse_categorical_accuracy: 0.9743 - scaled_adversarial_loss: 0.0629 - val_loss: 0.1887 - val_sparse_categorical_crossentropy: 0.1073 - val_sparse_categorical_accuracy: 0.9591 - val_scaled_adversarial_loss: 0.0814\n",
      "Epoch 742/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.1312 - sparse_categorical_crossentropy: 0.0690 - sparse_categorical_accuracy: 0.9756 - scaled_adversarial_loss: 0.0622 - val_loss: 0.1887 - val_sparse_categorical_crossentropy: 0.1038 - val_sparse_categorical_accuracy: 0.9554 - val_scaled_adversarial_loss: 0.0849\n",
      "Epoch 743/1000\n",
      "11/11 [==============================] - 4s 335ms/step - loss: 0.1379 - sparse_categorical_crossentropy: 0.0724 - sparse_categorical_accuracy: 0.9753 - scaled_adversarial_loss: 0.0655 - val_loss: 0.1910 - val_sparse_categorical_crossentropy: 0.1073 - val_sparse_categorical_accuracy: 0.9591 - val_scaled_adversarial_loss: 0.0837\n",
      "Epoch 744/1000\n",
      "11/11 [==============================] - 4s 332ms/step - loss: 0.1317 - sparse_categorical_crossentropy: 0.0664 - sparse_categorical_accuracy: 0.9753 - scaled_adversarial_loss: 0.0653 - val_loss: 0.1926 - val_sparse_categorical_crossentropy: 0.1103 - val_sparse_categorical_accuracy: 0.9569 - val_scaled_adversarial_loss: 0.0823\n",
      "Epoch 745/1000\n",
      "11/11 [==============================] - 4s 342ms/step - loss: 0.1380 - sparse_categorical_crossentropy: 0.0723 - sparse_categorical_accuracy: 0.9762 - scaled_adversarial_loss: 0.0657 - val_loss: 0.2003 - val_sparse_categorical_crossentropy: 0.1121 - val_sparse_categorical_accuracy: 0.9576 - val_scaled_adversarial_loss: 0.0883\n",
      "Epoch 746/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.1353 - sparse_categorical_crossentropy: 0.0682 - sparse_categorical_accuracy: 0.9762 - scaled_adversarial_loss: 0.0671 - val_loss: 0.2060 - val_sparse_categorical_crossentropy: 0.1153 - val_sparse_categorical_accuracy: 0.9569 - val_scaled_adversarial_loss: 0.0906\n",
      "Epoch 747/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.1312 - sparse_categorical_crossentropy: 0.0696 - sparse_categorical_accuracy: 0.9766 - scaled_adversarial_loss: 0.0615 - val_loss: 0.1861 - val_sparse_categorical_crossentropy: 0.1037 - val_sparse_categorical_accuracy: 0.9561 - val_scaled_adversarial_loss: 0.0823\n",
      "Epoch 748/1000\n",
      "11/11 [==============================] - 4s 335ms/step - loss: 0.1331 - sparse_categorical_crossentropy: 0.0664 - sparse_categorical_accuracy: 0.9784 - scaled_adversarial_loss: 0.0667 - val_loss: 0.1845 - val_sparse_categorical_crossentropy: 0.1052 - val_sparse_categorical_accuracy: 0.9606 - val_scaled_adversarial_loss: 0.0794\n",
      "Epoch 749/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.1290 - sparse_categorical_crossentropy: 0.0673 - sparse_categorical_accuracy: 0.9760 - scaled_adversarial_loss: 0.0618 - val_loss: 0.1799 - val_sparse_categorical_crossentropy: 0.1027 - val_sparse_categorical_accuracy: 0.9576 - val_scaled_adversarial_loss: 0.0772\n",
      "Epoch 750/1000\n",
      "11/11 [==============================] - 4s 332ms/step - loss: 0.1336 - sparse_categorical_crossentropy: 0.0700 - sparse_categorical_accuracy: 0.9775 - scaled_adversarial_loss: 0.0635 - val_loss: 0.1834 - val_sparse_categorical_crossentropy: 0.1071 - val_sparse_categorical_accuracy: 0.9554 - val_scaled_adversarial_loss: 0.0763\n",
      "Epoch 751/1000\n",
      "11/11 [==============================] - 4s 331ms/step - loss: 0.1297 - sparse_categorical_crossentropy: 0.0655 - sparse_categorical_accuracy: 0.9795 - scaled_adversarial_loss: 0.0641 - val_loss: 0.1806 - val_sparse_categorical_crossentropy: 0.1076 - val_sparse_categorical_accuracy: 0.9591 - val_scaled_adversarial_loss: 0.0730\n",
      "Epoch 752/1000\n",
      "11/11 [==============================] - 4s 337ms/step - loss: 0.1385 - sparse_categorical_crossentropy: 0.0724 - sparse_categorical_accuracy: 0.9758 - scaled_adversarial_loss: 0.0661 - val_loss: 0.1857 - val_sparse_categorical_crossentropy: 0.1117 - val_sparse_categorical_accuracy: 0.9561 - val_scaled_adversarial_loss: 0.0740\n",
      "Epoch 753/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.1305 - sparse_categorical_crossentropy: 0.0678 - sparse_categorical_accuracy: 0.9768 - scaled_adversarial_loss: 0.0627 - val_loss: 0.2014 - val_sparse_categorical_crossentropy: 0.1219 - val_sparse_categorical_accuracy: 0.9569 - val_scaled_adversarial_loss: 0.0795\n",
      "Epoch 754/1000\n",
      "11/11 [==============================] - 4s 335ms/step - loss: 0.1380 - sparse_categorical_crossentropy: 0.0713 - sparse_categorical_accuracy: 0.9755 - scaled_adversarial_loss: 0.0667 - val_loss: 0.1949 - val_sparse_categorical_crossentropy: 0.1126 - val_sparse_categorical_accuracy: 0.9599 - val_scaled_adversarial_loss: 0.0823\n",
      "Epoch 755/1000\n",
      "11/11 [==============================] - 4s 332ms/step - loss: 0.1328 - sparse_categorical_crossentropy: 0.0694 - sparse_categorical_accuracy: 0.9764 - scaled_adversarial_loss: 0.0634 - val_loss: 0.2077 - val_sparse_categorical_crossentropy: 0.1131 - val_sparse_categorical_accuracy: 0.9599 - val_scaled_adversarial_loss: 0.0946\n",
      "Epoch 756/1000\n",
      "11/11 [==============================] - 4s 335ms/step - loss: 0.1346 - sparse_categorical_crossentropy: 0.0691 - sparse_categorical_accuracy: 0.9725 - scaled_adversarial_loss: 0.0656 - val_loss: 0.2143 - val_sparse_categorical_crossentropy: 0.1221 - val_sparse_categorical_accuracy: 0.9554 - val_scaled_adversarial_loss: 0.0921\n",
      "Epoch 757/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.1409 - sparse_categorical_crossentropy: 0.0724 - sparse_categorical_accuracy: 0.9738 - scaled_adversarial_loss: 0.0685 - val_loss: 0.2069 - val_sparse_categorical_crossentropy: 0.1195 - val_sparse_categorical_accuracy: 0.9606 - val_scaled_adversarial_loss: 0.0875\n",
      "Epoch 758/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.1382 - sparse_categorical_crossentropy: 0.0741 - sparse_categorical_accuracy: 0.9764 - scaled_adversarial_loss: 0.0641 - val_loss: 0.1816 - val_sparse_categorical_crossentropy: 0.1029 - val_sparse_categorical_accuracy: 0.9621 - val_scaled_adversarial_loss: 0.0787\n",
      "Epoch 759/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.1381 - sparse_categorical_crossentropy: 0.0719 - sparse_categorical_accuracy: 0.9742 - scaled_adversarial_loss: 0.0663 - val_loss: 0.1845 - val_sparse_categorical_crossentropy: 0.1101 - val_sparse_categorical_accuracy: 0.9606 - val_scaled_adversarial_loss: 0.0744\n",
      "Epoch 760/1000\n",
      "11/11 [==============================] - 4s 338ms/step - loss: 0.1356 - sparse_categorical_crossentropy: 0.0684 - sparse_categorical_accuracy: 0.9743 - scaled_adversarial_loss: 0.0672 - val_loss: 0.1773 - val_sparse_categorical_crossentropy: 0.1049 - val_sparse_categorical_accuracy: 0.9621 - val_scaled_adversarial_loss: 0.0724\n",
      "Epoch 761/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.1349 - sparse_categorical_crossentropy: 0.0716 - sparse_categorical_accuracy: 0.9740 - scaled_adversarial_loss: 0.0633 - val_loss: 0.1985 - val_sparse_categorical_crossentropy: 0.1040 - val_sparse_categorical_accuracy: 0.9628 - val_scaled_adversarial_loss: 0.0945\n",
      "Epoch 762/1000\n",
      "11/11 [==============================] - 4s 331ms/step - loss: 0.1365 - sparse_categorical_crossentropy: 0.0691 - sparse_categorical_accuracy: 0.9762 - scaled_adversarial_loss: 0.0673 - val_loss: 0.2062 - val_sparse_categorical_crossentropy: 0.1157 - val_sparse_categorical_accuracy: 0.9606 - val_scaled_adversarial_loss: 0.0905\n",
      "Epoch 763/1000\n",
      "11/11 [==============================] - 4s 383ms/step - loss: 0.1292 - sparse_categorical_crossentropy: 0.0665 - sparse_categorical_accuracy: 0.9768 - scaled_adversarial_loss: 0.0627 - val_loss: 0.2022 - val_sparse_categorical_crossentropy: 0.1067 - val_sparse_categorical_accuracy: 0.9636 - val_scaled_adversarial_loss: 0.0954\n",
      "Epoch 764/1000\n",
      "11/11 [==============================] - 4s 339ms/step - loss: 0.1329 - sparse_categorical_crossentropy: 0.0682 - sparse_categorical_accuracy: 0.9755 - scaled_adversarial_loss: 0.0647 - val_loss: 0.1877 - val_sparse_categorical_crossentropy: 0.1067 - val_sparse_categorical_accuracy: 0.9621 - val_scaled_adversarial_loss: 0.0810\n",
      "Epoch 765/1000\n",
      "11/11 [==============================] - 4s 340ms/step - loss: 0.1320 - sparse_categorical_crossentropy: 0.0705 - sparse_categorical_accuracy: 0.9766 - scaled_adversarial_loss: 0.0615 - val_loss: 0.1843 - val_sparse_categorical_crossentropy: 0.0999 - val_sparse_categorical_accuracy: 0.9636 - val_scaled_adversarial_loss: 0.0844\n",
      "Epoch 766/1000\n",
      "11/11 [==============================] - 4s 344ms/step - loss: 0.1305 - sparse_categorical_crossentropy: 0.0676 - sparse_categorical_accuracy: 0.9760 - scaled_adversarial_loss: 0.0629 - val_loss: 0.1998 - val_sparse_categorical_crossentropy: 0.1135 - val_sparse_categorical_accuracy: 0.9621 - val_scaled_adversarial_loss: 0.0863\n",
      "Epoch 767/1000\n",
      "11/11 [==============================] - 4s 344ms/step - loss: 0.1354 - sparse_categorical_crossentropy: 0.0675 - sparse_categorical_accuracy: 0.9781 - scaled_adversarial_loss: 0.0679 - val_loss: 0.1748 - val_sparse_categorical_crossentropy: 0.0974 - val_sparse_categorical_accuracy: 0.9591 - val_scaled_adversarial_loss: 0.0774\n",
      "Epoch 768/1000\n",
      "11/11 [==============================] - 4s 341ms/step - loss: 0.1339 - sparse_categorical_crossentropy: 0.0705 - sparse_categorical_accuracy: 0.9762 - scaled_adversarial_loss: 0.0634 - val_loss: 0.2022 - val_sparse_categorical_crossentropy: 0.1090 - val_sparse_categorical_accuracy: 0.9591 - val_scaled_adversarial_loss: 0.0931\n",
      "Epoch 769/1000\n",
      "11/11 [==============================] - 4s 342ms/step - loss: 0.1310 - sparse_categorical_crossentropy: 0.0661 - sparse_categorical_accuracy: 0.9751 - scaled_adversarial_loss: 0.0649 - val_loss: 0.1996 - val_sparse_categorical_crossentropy: 0.1116 - val_sparse_categorical_accuracy: 0.9613 - val_scaled_adversarial_loss: 0.0880\n",
      "Epoch 770/1000\n",
      "11/11 [==============================] - 4s 336ms/step - loss: 0.1360 - sparse_categorical_crossentropy: 0.0726 - sparse_categorical_accuracy: 0.9738 - scaled_adversarial_loss: 0.0633 - val_loss: 0.1929 - val_sparse_categorical_crossentropy: 0.1082 - val_sparse_categorical_accuracy: 0.9546 - val_scaled_adversarial_loss: 0.0847\n",
      "Epoch 771/1000\n",
      "11/11 [==============================] - 4s 337ms/step - loss: 0.1345 - sparse_categorical_crossentropy: 0.0717 - sparse_categorical_accuracy: 0.9764 - scaled_adversarial_loss: 0.0627 - val_loss: 0.1794 - val_sparse_categorical_crossentropy: 0.0992 - val_sparse_categorical_accuracy: 0.9621 - val_scaled_adversarial_loss: 0.0803\n",
      "Epoch 772/1000\n",
      "11/11 [==============================] - 4s 336ms/step - loss: 0.1230 - sparse_categorical_crossentropy: 0.0597 - sparse_categorical_accuracy: 0.9807 - scaled_adversarial_loss: 0.0633 - val_loss: 0.1915 - val_sparse_categorical_crossentropy: 0.1076 - val_sparse_categorical_accuracy: 0.9591 - val_scaled_adversarial_loss: 0.0838\n",
      "Epoch 773/1000\n",
      "11/11 [==============================] - 4s 335ms/step - loss: 0.1282 - sparse_categorical_crossentropy: 0.0635 - sparse_categorical_accuracy: 0.9771 - scaled_adversarial_loss: 0.0646 - val_loss: 0.1935 - val_sparse_categorical_crossentropy: 0.1096 - val_sparse_categorical_accuracy: 0.9591 - val_scaled_adversarial_loss: 0.0839\n",
      "Epoch 774/1000\n",
      "11/11 [==============================] - 4s 335ms/step - loss: 0.1295 - sparse_categorical_crossentropy: 0.0649 - sparse_categorical_accuracy: 0.9781 - scaled_adversarial_loss: 0.0646 - val_loss: 0.1794 - val_sparse_categorical_crossentropy: 0.1028 - val_sparse_categorical_accuracy: 0.9576 - val_scaled_adversarial_loss: 0.0766\n",
      "Epoch 775/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.1315 - sparse_categorical_crossentropy: 0.0670 - sparse_categorical_accuracy: 0.9775 - scaled_adversarial_loss: 0.0645 - val_loss: 0.1769 - val_sparse_categorical_crossentropy: 0.1014 - val_sparse_categorical_accuracy: 0.9561 - val_scaled_adversarial_loss: 0.0756\n",
      "Epoch 776/1000\n",
      "11/11 [==============================] - 4s 335ms/step - loss: 0.1293 - sparse_categorical_crossentropy: 0.0665 - sparse_categorical_accuracy: 0.9781 - scaled_adversarial_loss: 0.0628 - val_loss: 0.1849 - val_sparse_categorical_crossentropy: 0.1079 - val_sparse_categorical_accuracy: 0.9546 - val_scaled_adversarial_loss: 0.0770\n",
      "Epoch 777/1000\n",
      "11/11 [==============================] - 4s 335ms/step - loss: 0.1403 - sparse_categorical_crossentropy: 0.0745 - sparse_categorical_accuracy: 0.9760 - scaled_adversarial_loss: 0.0658 - val_loss: 0.1696 - val_sparse_categorical_crossentropy: 0.1019 - val_sparse_categorical_accuracy: 0.9561 - val_scaled_adversarial_loss: 0.0677\n",
      "Epoch 778/1000\n",
      "11/11 [==============================] - 4s 335ms/step - loss: 0.1312 - sparse_categorical_crossentropy: 0.0689 - sparse_categorical_accuracy: 0.9786 - scaled_adversarial_loss: 0.0623 - val_loss: 0.1619 - val_sparse_categorical_crossentropy: 0.0968 - val_sparse_categorical_accuracy: 0.9628 - val_scaled_adversarial_loss: 0.0651\n",
      "Epoch 779/1000\n",
      "11/11 [==============================] - 4s 337ms/step - loss: 0.1314 - sparse_categorical_crossentropy: 0.0684 - sparse_categorical_accuracy: 0.9756 - scaled_adversarial_loss: 0.0630 - val_loss: 0.1729 - val_sparse_categorical_crossentropy: 0.1011 - val_sparse_categorical_accuracy: 0.9651 - val_scaled_adversarial_loss: 0.0719\n",
      "Epoch 780/1000\n",
      "11/11 [==============================] - 4s 335ms/step - loss: 0.1277 - sparse_categorical_crossentropy: 0.0613 - sparse_categorical_accuracy: 0.9803 - scaled_adversarial_loss: 0.0664 - val_loss: 0.1795 - val_sparse_categorical_crossentropy: 0.1013 - val_sparse_categorical_accuracy: 0.9599 - val_scaled_adversarial_loss: 0.0782\n",
      "Epoch 781/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.1335 - sparse_categorical_crossentropy: 0.0704 - sparse_categorical_accuracy: 0.9769 - scaled_adversarial_loss: 0.0631 - val_loss: 0.1855 - val_sparse_categorical_crossentropy: 0.1079 - val_sparse_categorical_accuracy: 0.9599 - val_scaled_adversarial_loss: 0.0776\n",
      "Epoch 782/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.1328 - sparse_categorical_crossentropy: 0.0681 - sparse_categorical_accuracy: 0.9769 - scaled_adversarial_loss: 0.0647 - val_loss: 0.1806 - val_sparse_categorical_crossentropy: 0.1014 - val_sparse_categorical_accuracy: 0.9606 - val_scaled_adversarial_loss: 0.0791\n",
      "Epoch 783/1000\n",
      "11/11 [==============================] - 4s 335ms/step - loss: 0.1289 - sparse_categorical_crossentropy: 0.0641 - sparse_categorical_accuracy: 0.9777 - scaled_adversarial_loss: 0.0648 - val_loss: 0.1860 - val_sparse_categorical_crossentropy: 0.1068 - val_sparse_categorical_accuracy: 0.9613 - val_scaled_adversarial_loss: 0.0792\n",
      "Epoch 784/1000\n",
      "11/11 [==============================] - 4s 335ms/step - loss: 0.1319 - sparse_categorical_crossentropy: 0.0674 - sparse_categorical_accuracy: 0.9775 - scaled_adversarial_loss: 0.0645 - val_loss: 0.1984 - val_sparse_categorical_crossentropy: 0.1086 - val_sparse_categorical_accuracy: 0.9591 - val_scaled_adversarial_loss: 0.0898\n",
      "Epoch 785/1000\n",
      "11/11 [==============================] - 4s 335ms/step - loss: 0.1249 - sparse_categorical_crossentropy: 0.0642 - sparse_categorical_accuracy: 0.9779 - scaled_adversarial_loss: 0.0607 - val_loss: 0.1902 - val_sparse_categorical_crossentropy: 0.1106 - val_sparse_categorical_accuracy: 0.9576 - val_scaled_adversarial_loss: 0.0796\n",
      "Epoch 786/1000\n",
      "11/11 [==============================] - 4s 342ms/step - loss: 0.1277 - sparse_categorical_crossentropy: 0.0652 - sparse_categorical_accuracy: 0.9792 - scaled_adversarial_loss: 0.0625 - val_loss: 0.1755 - val_sparse_categorical_crossentropy: 0.1033 - val_sparse_categorical_accuracy: 0.9584 - val_scaled_adversarial_loss: 0.0722\n",
      "Epoch 787/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.1268 - sparse_categorical_crossentropy: 0.0650 - sparse_categorical_accuracy: 0.9782 - scaled_adversarial_loss: 0.0618 - val_loss: 0.1767 - val_sparse_categorical_crossentropy: 0.1052 - val_sparse_categorical_accuracy: 0.9621 - val_scaled_adversarial_loss: 0.0715\n",
      "Epoch 788/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.1263 - sparse_categorical_crossentropy: 0.0648 - sparse_categorical_accuracy: 0.9773 - scaled_adversarial_loss: 0.0615 - val_loss: 0.1787 - val_sparse_categorical_crossentropy: 0.1099 - val_sparse_categorical_accuracy: 0.9569 - val_scaled_adversarial_loss: 0.0688\n",
      "Epoch 789/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.1268 - sparse_categorical_crossentropy: 0.0602 - sparse_categorical_accuracy: 0.9797 - scaled_adversarial_loss: 0.0666 - val_loss: 0.1859 - val_sparse_categorical_crossentropy: 0.1061 - val_sparse_categorical_accuracy: 0.9599 - val_scaled_adversarial_loss: 0.0798\n",
      "Epoch 790/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.1267 - sparse_categorical_crossentropy: 0.0633 - sparse_categorical_accuracy: 0.9784 - scaled_adversarial_loss: 0.0634 - val_loss: 0.1855 - val_sparse_categorical_crossentropy: 0.1044 - val_sparse_categorical_accuracy: 0.9591 - val_scaled_adversarial_loss: 0.0810\n",
      "Epoch 791/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.1206 - sparse_categorical_crossentropy: 0.0615 - sparse_categorical_accuracy: 0.9788 - scaled_adversarial_loss: 0.0591 - val_loss: 0.1756 - val_sparse_categorical_crossentropy: 0.1031 - val_sparse_categorical_accuracy: 0.9591 - val_scaled_adversarial_loss: 0.0725\n",
      "Epoch 792/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.1278 - sparse_categorical_crossentropy: 0.0636 - sparse_categorical_accuracy: 0.9790 - scaled_adversarial_loss: 0.0642 - val_loss: 0.1966 - val_sparse_categorical_crossentropy: 0.1112 - val_sparse_categorical_accuracy: 0.9584 - val_scaled_adversarial_loss: 0.0855\n",
      "Epoch 793/1000\n",
      "11/11 [==============================] - 4s 340ms/step - loss: 0.1278 - sparse_categorical_crossentropy: 0.0633 - sparse_categorical_accuracy: 0.9790 - scaled_adversarial_loss: 0.0644 - val_loss: 0.1978 - val_sparse_categorical_crossentropy: 0.1158 - val_sparse_categorical_accuracy: 0.9561 - val_scaled_adversarial_loss: 0.0819\n",
      "Epoch 794/1000\n",
      "11/11 [==============================] - 4s 337ms/step - loss: 0.1320 - sparse_categorical_crossentropy: 0.0664 - sparse_categorical_accuracy: 0.9766 - scaled_adversarial_loss: 0.0656 - val_loss: 0.1953 - val_sparse_categorical_crossentropy: 0.1075 - val_sparse_categorical_accuracy: 0.9628 - val_scaled_adversarial_loss: 0.0878\n",
      "Epoch 795/1000\n",
      "11/11 [==============================] - 4s 337ms/step - loss: 0.1239 - sparse_categorical_crossentropy: 0.0616 - sparse_categorical_accuracy: 0.9788 - scaled_adversarial_loss: 0.0624 - val_loss: 0.1986 - val_sparse_categorical_crossentropy: 0.1127 - val_sparse_categorical_accuracy: 0.9599 - val_scaled_adversarial_loss: 0.0859\n",
      "Epoch 796/1000\n",
      "11/11 [==============================] - 4s 343ms/step - loss: 0.1274 - sparse_categorical_crossentropy: 0.0645 - sparse_categorical_accuracy: 0.9782 - scaled_adversarial_loss: 0.0629 - val_loss: 0.2052 - val_sparse_categorical_crossentropy: 0.1208 - val_sparse_categorical_accuracy: 0.9524 - val_scaled_adversarial_loss: 0.0844\n",
      "Epoch 797/1000\n",
      "11/11 [==============================] - 4s 335ms/step - loss: 0.1313 - sparse_categorical_crossentropy: 0.0702 - sparse_categorical_accuracy: 0.9751 - scaled_adversarial_loss: 0.0611 - val_loss: 0.1779 - val_sparse_categorical_crossentropy: 0.1017 - val_sparse_categorical_accuracy: 0.9599 - val_scaled_adversarial_loss: 0.0762\n",
      "Epoch 798/1000\n",
      "11/11 [==============================] - 4s 336ms/step - loss: 0.1345 - sparse_categorical_crossentropy: 0.0696 - sparse_categorical_accuracy: 0.9773 - scaled_adversarial_loss: 0.0649 - val_loss: 0.1999 - val_sparse_categorical_crossentropy: 0.1147 - val_sparse_categorical_accuracy: 0.9569 - val_scaled_adversarial_loss: 0.0852\n",
      "Epoch 799/1000\n",
      "11/11 [==============================] - 4s 335ms/step - loss: 0.1310 - sparse_categorical_crossentropy: 0.0694 - sparse_categorical_accuracy: 0.9732 - scaled_adversarial_loss: 0.0616 - val_loss: 0.1827 - val_sparse_categorical_crossentropy: 0.1067 - val_sparse_categorical_accuracy: 0.9613 - val_scaled_adversarial_loss: 0.0760\n",
      "Epoch 800/1000\n",
      "11/11 [==============================] - 4s 336ms/step - loss: 0.1329 - sparse_categorical_crossentropy: 0.0688 - sparse_categorical_accuracy: 0.9775 - scaled_adversarial_loss: 0.0641 - val_loss: 0.1896 - val_sparse_categorical_crossentropy: 0.1135 - val_sparse_categorical_accuracy: 0.9599 - val_scaled_adversarial_loss: 0.0761\n",
      "Epoch 801/1000\n",
      "11/11 [==============================] - 4s 336ms/step - loss: 0.1309 - sparse_categorical_crossentropy: 0.0672 - sparse_categorical_accuracy: 0.9747 - scaled_adversarial_loss: 0.0637 - val_loss: 0.1940 - val_sparse_categorical_crossentropy: 0.1099 - val_sparse_categorical_accuracy: 0.9591 - val_scaled_adversarial_loss: 0.0841\n",
      "Epoch 802/1000\n",
      "11/11 [==============================] - 4s 336ms/step - loss: 0.1281 - sparse_categorical_crossentropy: 0.0644 - sparse_categorical_accuracy: 0.9801 - scaled_adversarial_loss: 0.0637 - val_loss: 0.1847 - val_sparse_categorical_crossentropy: 0.1124 - val_sparse_categorical_accuracy: 0.9569 - val_scaled_adversarial_loss: 0.0723\n",
      "Epoch 803/1000\n",
      "11/11 [==============================] - 4s 338ms/step - loss: 0.1228 - sparse_categorical_crossentropy: 0.0611 - sparse_categorical_accuracy: 0.9766 - scaled_adversarial_loss: 0.0617 - val_loss: 0.1857 - val_sparse_categorical_crossentropy: 0.1065 - val_sparse_categorical_accuracy: 0.9599 - val_scaled_adversarial_loss: 0.0791\n",
      "Epoch 804/1000\n",
      "11/11 [==============================] - 4s 335ms/step - loss: 0.1318 - sparse_categorical_crossentropy: 0.0682 - sparse_categorical_accuracy: 0.9747 - scaled_adversarial_loss: 0.0636 - val_loss: 0.1929 - val_sparse_categorical_crossentropy: 0.1152 - val_sparse_categorical_accuracy: 0.9599 - val_scaled_adversarial_loss: 0.0777\n",
      "Epoch 805/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.1226 - sparse_categorical_crossentropy: 0.0610 - sparse_categorical_accuracy: 0.9779 - scaled_adversarial_loss: 0.0617 - val_loss: 0.1763 - val_sparse_categorical_crossentropy: 0.1018 - val_sparse_categorical_accuracy: 0.9621 - val_scaled_adversarial_loss: 0.0745\n",
      "Epoch 806/1000\n",
      "11/11 [==============================] - 4s 336ms/step - loss: 0.1238 - sparse_categorical_crossentropy: 0.0618 - sparse_categorical_accuracy: 0.9779 - scaled_adversarial_loss: 0.0621 - val_loss: 0.1851 - val_sparse_categorical_crossentropy: 0.1087 - val_sparse_categorical_accuracy: 0.9561 - val_scaled_adversarial_loss: 0.0764\n",
      "Epoch 807/1000\n",
      "11/11 [==============================] - 4s 337ms/step - loss: 0.1310 - sparse_categorical_crossentropy: 0.0658 - sparse_categorical_accuracy: 0.9773 - scaled_adversarial_loss: 0.0652 - val_loss: 0.1838 - val_sparse_categorical_crossentropy: 0.1020 - val_sparse_categorical_accuracy: 0.9554 - val_scaled_adversarial_loss: 0.0818\n",
      "Epoch 808/1000\n",
      "11/11 [==============================] - 4s 336ms/step - loss: 0.1234 - sparse_categorical_crossentropy: 0.0619 - sparse_categorical_accuracy: 0.9777 - scaled_adversarial_loss: 0.0615 - val_loss: 0.1946 - val_sparse_categorical_crossentropy: 0.1107 - val_sparse_categorical_accuracy: 0.9576 - val_scaled_adversarial_loss: 0.0839\n",
      "Epoch 809/1000\n",
      "11/11 [==============================] - 4s 335ms/step - loss: 0.1274 - sparse_categorical_crossentropy: 0.0653 - sparse_categorical_accuracy: 0.9782 - scaled_adversarial_loss: 0.0620 - val_loss: 0.2005 - val_sparse_categorical_crossentropy: 0.1092 - val_sparse_categorical_accuracy: 0.9606 - val_scaled_adversarial_loss: 0.0913\n",
      "Epoch 810/1000\n",
      "11/11 [==============================] - 4s 337ms/step - loss: 0.1374 - sparse_categorical_crossentropy: 0.0714 - sparse_categorical_accuracy: 0.9762 - scaled_adversarial_loss: 0.0661 - val_loss: 0.1801 - val_sparse_categorical_crossentropy: 0.0990 - val_sparse_categorical_accuracy: 0.9606 - val_scaled_adversarial_loss: 0.0811\n",
      "Epoch 811/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.1266 - sparse_categorical_crossentropy: 0.0652 - sparse_categorical_accuracy: 0.9781 - scaled_adversarial_loss: 0.0613 - val_loss: 0.1904 - val_sparse_categorical_crossentropy: 0.1050 - val_sparse_categorical_accuracy: 0.9576 - val_scaled_adversarial_loss: 0.0854\n",
      "Epoch 812/1000\n",
      "11/11 [==============================] - 4s 335ms/step - loss: 0.1300 - sparse_categorical_crossentropy: 0.0646 - sparse_categorical_accuracy: 0.9792 - scaled_adversarial_loss: 0.0654 - val_loss: 0.2126 - val_sparse_categorical_crossentropy: 0.1201 - val_sparse_categorical_accuracy: 0.9606 - val_scaled_adversarial_loss: 0.0925\n",
      "Epoch 813/1000\n",
      "11/11 [==============================] - 4s 335ms/step - loss: 0.1295 - sparse_categorical_crossentropy: 0.0650 - sparse_categorical_accuracy: 0.9764 - scaled_adversarial_loss: 0.0645 - val_loss: 0.1838 - val_sparse_categorical_crossentropy: 0.1005 - val_sparse_categorical_accuracy: 0.9628 - val_scaled_adversarial_loss: 0.0832\n",
      "Epoch 814/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.1353 - sparse_categorical_crossentropy: 0.0716 - sparse_categorical_accuracy: 0.9751 - scaled_adversarial_loss: 0.0637 - val_loss: 0.2040 - val_sparse_categorical_crossentropy: 0.1164 - val_sparse_categorical_accuracy: 0.9599 - val_scaled_adversarial_loss: 0.0876\n",
      "Epoch 815/1000\n",
      "11/11 [==============================] - 4s 335ms/step - loss: 0.1286 - sparse_categorical_crossentropy: 0.0632 - sparse_categorical_accuracy: 0.9781 - scaled_adversarial_loss: 0.0655 - val_loss: 0.2184 - val_sparse_categorical_crossentropy: 0.1230 - val_sparse_categorical_accuracy: 0.9576 - val_scaled_adversarial_loss: 0.0954\n",
      "Epoch 816/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.1314 - sparse_categorical_crossentropy: 0.0688 - sparse_categorical_accuracy: 0.9758 - scaled_adversarial_loss: 0.0626 - val_loss: 0.1771 - val_sparse_categorical_crossentropy: 0.1037 - val_sparse_categorical_accuracy: 0.9606 - val_scaled_adversarial_loss: 0.0733\n",
      "Epoch 817/1000\n",
      "11/11 [==============================] - 4s 335ms/step - loss: 0.1302 - sparse_categorical_crossentropy: 0.0663 - sparse_categorical_accuracy: 0.9792 - scaled_adversarial_loss: 0.0638 - val_loss: 0.1820 - val_sparse_categorical_crossentropy: 0.1076 - val_sparse_categorical_accuracy: 0.9613 - val_scaled_adversarial_loss: 0.0744\n",
      "Epoch 818/1000\n",
      "11/11 [==============================] - 4s 340ms/step - loss: 0.1304 - sparse_categorical_crossentropy: 0.0668 - sparse_categorical_accuracy: 0.9775 - scaled_adversarial_loss: 0.0636 - val_loss: 0.1941 - val_sparse_categorical_crossentropy: 0.1150 - val_sparse_categorical_accuracy: 0.9584 - val_scaled_adversarial_loss: 0.0791\n",
      "Epoch 819/1000\n",
      "11/11 [==============================] - 4s 336ms/step - loss: 0.1343 - sparse_categorical_crossentropy: 0.0681 - sparse_categorical_accuracy: 0.9775 - scaled_adversarial_loss: 0.0662 - val_loss: 0.1825 - val_sparse_categorical_crossentropy: 0.1065 - val_sparse_categorical_accuracy: 0.9569 - val_scaled_adversarial_loss: 0.0761\n",
      "Epoch 820/1000\n",
      "11/11 [==============================] - 4s 335ms/step - loss: 0.1284 - sparse_categorical_crossentropy: 0.0665 - sparse_categorical_accuracy: 0.9764 - scaled_adversarial_loss: 0.0619 - val_loss: 0.1768 - val_sparse_categorical_crossentropy: 0.1006 - val_sparse_categorical_accuracy: 0.9613 - val_scaled_adversarial_loss: 0.0762\n",
      "Epoch 821/1000\n",
      "11/11 [==============================] - 4s 337ms/step - loss: 0.1270 - sparse_categorical_crossentropy: 0.0629 - sparse_categorical_accuracy: 0.9782 - scaled_adversarial_loss: 0.0641 - val_loss: 0.1854 - val_sparse_categorical_crossentropy: 0.1078 - val_sparse_categorical_accuracy: 0.9584 - val_scaled_adversarial_loss: 0.0776\n",
      "Epoch 822/1000\n",
      "11/11 [==============================] - 4s 341ms/step - loss: 0.1268 - sparse_categorical_crossentropy: 0.0619 - sparse_categorical_accuracy: 0.9788 - scaled_adversarial_loss: 0.0649 - val_loss: 0.1804 - val_sparse_categorical_crossentropy: 0.1008 - val_sparse_categorical_accuracy: 0.9636 - val_scaled_adversarial_loss: 0.0797\n",
      "Epoch 823/1000\n",
      "11/11 [==============================] - 4s 343ms/step - loss: 0.1213 - sparse_categorical_crossentropy: 0.0597 - sparse_categorical_accuracy: 0.9799 - scaled_adversarial_loss: 0.0616 - val_loss: 0.1899 - val_sparse_categorical_crossentropy: 0.1105 - val_sparse_categorical_accuracy: 0.9569 - val_scaled_adversarial_loss: 0.0793\n",
      "Epoch 824/1000\n",
      "11/11 [==============================] - 4s 342ms/step - loss: 0.1295 - sparse_categorical_crossentropy: 0.0639 - sparse_categorical_accuracy: 0.9803 - scaled_adversarial_loss: 0.0656 - val_loss: 0.1849 - val_sparse_categorical_crossentropy: 0.1040 - val_sparse_categorical_accuracy: 0.9621 - val_scaled_adversarial_loss: 0.0809\n",
      "Epoch 825/1000\n",
      "11/11 [==============================] - 4s 344ms/step - loss: 0.1221 - sparse_categorical_crossentropy: 0.0599 - sparse_categorical_accuracy: 0.9799 - scaled_adversarial_loss: 0.0622 - val_loss: 0.1877 - val_sparse_categorical_crossentropy: 0.1096 - val_sparse_categorical_accuracy: 0.9621 - val_scaled_adversarial_loss: 0.0781\n",
      "Epoch 826/1000\n",
      "11/11 [==============================] - 4s 344ms/step - loss: 0.1266 - sparse_categorical_crossentropy: 0.0618 - sparse_categorical_accuracy: 0.9792 - scaled_adversarial_loss: 0.0648 - val_loss: 0.1749 - val_sparse_categorical_crossentropy: 0.1014 - val_sparse_categorical_accuracy: 0.9569 - val_scaled_adversarial_loss: 0.0735\n",
      "Epoch 827/1000\n",
      "11/11 [==============================] - 4s 341ms/step - loss: 0.1344 - sparse_categorical_crossentropy: 0.0718 - sparse_categorical_accuracy: 0.9736 - scaled_adversarial_loss: 0.0626 - val_loss: 0.1773 - val_sparse_categorical_crossentropy: 0.1016 - val_sparse_categorical_accuracy: 0.9584 - val_scaled_adversarial_loss: 0.0757\n",
      "Epoch 828/1000\n",
      "11/11 [==============================] - 4s 338ms/step - loss: 0.1311 - sparse_categorical_crossentropy: 0.0663 - sparse_categorical_accuracy: 0.9762 - scaled_adversarial_loss: 0.0649 - val_loss: 0.1769 - val_sparse_categorical_crossentropy: 0.0973 - val_sparse_categorical_accuracy: 0.9636 - val_scaled_adversarial_loss: 0.0796\n",
      "Epoch 829/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.1258 - sparse_categorical_crossentropy: 0.0648 - sparse_categorical_accuracy: 0.9779 - scaled_adversarial_loss: 0.0610 - val_loss: 0.1820 - val_sparse_categorical_crossentropy: 0.1026 - val_sparse_categorical_accuracy: 0.9599 - val_scaled_adversarial_loss: 0.0794\n",
      "Epoch 830/1000\n",
      "11/11 [==============================] - 4s 337ms/step - loss: 0.1284 - sparse_categorical_crossentropy: 0.0652 - sparse_categorical_accuracy: 0.9794 - scaled_adversarial_loss: 0.0632 - val_loss: 0.1741 - val_sparse_categorical_crossentropy: 0.0999 - val_sparse_categorical_accuracy: 0.9636 - val_scaled_adversarial_loss: 0.0742\n",
      "Epoch 831/1000\n",
      "11/11 [==============================] - 4s 343ms/step - loss: 0.1257 - sparse_categorical_crossentropy: 0.0640 - sparse_categorical_accuracy: 0.9764 - scaled_adversarial_loss: 0.0616 - val_loss: 0.1810 - val_sparse_categorical_crossentropy: 0.1017 - val_sparse_categorical_accuracy: 0.9621 - val_scaled_adversarial_loss: 0.0793\n",
      "Epoch 832/1000\n",
      "11/11 [==============================] - 4s 337ms/step - loss: 0.1259 - sparse_categorical_crossentropy: 0.0603 - sparse_categorical_accuracy: 0.9795 - scaled_adversarial_loss: 0.0656 - val_loss: 0.1839 - val_sparse_categorical_crossentropy: 0.1081 - val_sparse_categorical_accuracy: 0.9599 - val_scaled_adversarial_loss: 0.0758\n",
      "Epoch 833/1000\n",
      "11/11 [==============================] - 4s 338ms/step - loss: 0.1282 - sparse_categorical_crossentropy: 0.0657 - sparse_categorical_accuracy: 0.9788 - scaled_adversarial_loss: 0.0625 - val_loss: 0.1849 - val_sparse_categorical_crossentropy: 0.1087 - val_sparse_categorical_accuracy: 0.9599 - val_scaled_adversarial_loss: 0.0763\n",
      "Epoch 834/1000\n",
      "11/11 [==============================] - 4s 338ms/step - loss: 0.1276 - sparse_categorical_crossentropy: 0.0658 - sparse_categorical_accuracy: 0.9775 - scaled_adversarial_loss: 0.0618 - val_loss: 0.1713 - val_sparse_categorical_crossentropy: 0.0998 - val_sparse_categorical_accuracy: 0.9613 - val_scaled_adversarial_loss: 0.0715\n",
      "Epoch 835/1000\n",
      "11/11 [==============================] - 4s 337ms/step - loss: 0.1261 - sparse_categorical_crossentropy: 0.0645 - sparse_categorical_accuracy: 0.9781 - scaled_adversarial_loss: 0.0616 - val_loss: 0.1828 - val_sparse_categorical_crossentropy: 0.1044 - val_sparse_categorical_accuracy: 0.9651 - val_scaled_adversarial_loss: 0.0784\n",
      "Epoch 836/1000\n",
      "11/11 [==============================] - 4s 335ms/step - loss: 0.1250 - sparse_categorical_crossentropy: 0.0608 - sparse_categorical_accuracy: 0.9792 - scaled_adversarial_loss: 0.0642 - val_loss: 0.1893 - val_sparse_categorical_crossentropy: 0.1094 - val_sparse_categorical_accuracy: 0.9584 - val_scaled_adversarial_loss: 0.0798\n",
      "Epoch 837/1000\n",
      "11/11 [==============================] - 4s 343ms/step - loss: 0.1307 - sparse_categorical_crossentropy: 0.0675 - sparse_categorical_accuracy: 0.9782 - scaled_adversarial_loss: 0.0633 - val_loss: 0.1737 - val_sparse_categorical_crossentropy: 0.0995 - val_sparse_categorical_accuracy: 0.9628 - val_scaled_adversarial_loss: 0.0742\n",
      "Epoch 838/1000\n",
      "11/11 [==============================] - 4s 337ms/step - loss: 0.1226 - sparse_categorical_crossentropy: 0.0611 - sparse_categorical_accuracy: 0.9788 - scaled_adversarial_loss: 0.0615 - val_loss: 0.1697 - val_sparse_categorical_crossentropy: 0.0978 - val_sparse_categorical_accuracy: 0.9584 - val_scaled_adversarial_loss: 0.0719\n",
      "Epoch 839/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.1236 - sparse_categorical_crossentropy: 0.0639 - sparse_categorical_accuracy: 0.9797 - scaled_adversarial_loss: 0.0596 - val_loss: 0.1743 - val_sparse_categorical_crossentropy: 0.1009 - val_sparse_categorical_accuracy: 0.9599 - val_scaled_adversarial_loss: 0.0733\n",
      "Epoch 840/1000\n",
      "11/11 [==============================] - 4s 335ms/step - loss: 0.1316 - sparse_categorical_crossentropy: 0.0646 - sparse_categorical_accuracy: 0.9782 - scaled_adversarial_loss: 0.0670 - val_loss: 0.1752 - val_sparse_categorical_crossentropy: 0.1062 - val_sparse_categorical_accuracy: 0.9584 - val_scaled_adversarial_loss: 0.0690\n",
      "Epoch 841/1000\n",
      "11/11 [==============================] - 4s 336ms/step - loss: 0.1211 - sparse_categorical_crossentropy: 0.0609 - sparse_categorical_accuracy: 0.9803 - scaled_adversarial_loss: 0.0602 - val_loss: 0.1781 - val_sparse_categorical_crossentropy: 0.1028 - val_sparse_categorical_accuracy: 0.9591 - val_scaled_adversarial_loss: 0.0753\n",
      "Epoch 842/1000\n",
      "11/11 [==============================] - 4s 337ms/step - loss: 0.1273 - sparse_categorical_crossentropy: 0.0660 - sparse_categorical_accuracy: 0.9768 - scaled_adversarial_loss: 0.0613 - val_loss: 0.1909 - val_sparse_categorical_crossentropy: 0.1112 - val_sparse_categorical_accuracy: 0.9561 - val_scaled_adversarial_loss: 0.0797\n",
      "Epoch 843/1000\n",
      "11/11 [==============================] - 4s 336ms/step - loss: 0.1324 - sparse_categorical_crossentropy: 0.0691 - sparse_categorical_accuracy: 0.9782 - scaled_adversarial_loss: 0.0633 - val_loss: 0.1946 - val_sparse_categorical_crossentropy: 0.1103 - val_sparse_categorical_accuracy: 0.9576 - val_scaled_adversarial_loss: 0.0843\n",
      "Epoch 844/1000\n",
      "11/11 [==============================] - 4s 336ms/step - loss: 0.1304 - sparse_categorical_crossentropy: 0.0665 - sparse_categorical_accuracy: 0.9786 - scaled_adversarial_loss: 0.0640 - val_loss: 0.1909 - val_sparse_categorical_crossentropy: 0.1097 - val_sparse_categorical_accuracy: 0.9561 - val_scaled_adversarial_loss: 0.0812\n",
      "Epoch 845/1000\n",
      "11/11 [==============================] - 4s 336ms/step - loss: 0.1302 - sparse_categorical_crossentropy: 0.0675 - sparse_categorical_accuracy: 0.9777 - scaled_adversarial_loss: 0.0627 - val_loss: 0.1761 - val_sparse_categorical_crossentropy: 0.0980 - val_sparse_categorical_accuracy: 0.9613 - val_scaled_adversarial_loss: 0.0780\n",
      "Epoch 846/1000\n",
      "11/11 [==============================] - 4s 336ms/step - loss: 0.1251 - sparse_categorical_crossentropy: 0.0629 - sparse_categorical_accuracy: 0.9790 - scaled_adversarial_loss: 0.0622 - val_loss: 0.1872 - val_sparse_categorical_crossentropy: 0.1062 - val_sparse_categorical_accuracy: 0.9569 - val_scaled_adversarial_loss: 0.0809\n",
      "Epoch 847/1000\n",
      "11/11 [==============================] - 4s 338ms/step - loss: 0.1255 - sparse_categorical_crossentropy: 0.0633 - sparse_categorical_accuracy: 0.9784 - scaled_adversarial_loss: 0.0622 - val_loss: 0.1958 - val_sparse_categorical_crossentropy: 0.1158 - val_sparse_categorical_accuracy: 0.9613 - val_scaled_adversarial_loss: 0.0801\n",
      "Epoch 848/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.1217 - sparse_categorical_crossentropy: 0.0596 - sparse_categorical_accuracy: 0.9794 - scaled_adversarial_loss: 0.0621 - val_loss: 0.1950 - val_sparse_categorical_crossentropy: 0.1193 - val_sparse_categorical_accuracy: 0.9584 - val_scaled_adversarial_loss: 0.0756\n",
      "Epoch 849/1000\n",
      "11/11 [==============================] - 4s 335ms/step - loss: 0.1253 - sparse_categorical_crossentropy: 0.0629 - sparse_categorical_accuracy: 0.9790 - scaled_adversarial_loss: 0.0623 - val_loss: 0.1970 - val_sparse_categorical_crossentropy: 0.1103 - val_sparse_categorical_accuracy: 0.9591 - val_scaled_adversarial_loss: 0.0867\n",
      "Epoch 850/1000\n",
      "11/11 [==============================] - 4s 338ms/step - loss: 0.1303 - sparse_categorical_crossentropy: 0.0642 - sparse_categorical_accuracy: 0.9803 - scaled_adversarial_loss: 0.0661 - val_loss: 0.1763 - val_sparse_categorical_crossentropy: 0.1060 - val_sparse_categorical_accuracy: 0.9643 - val_scaled_adversarial_loss: 0.0704\n",
      "Epoch 851/1000\n",
      "11/11 [==============================] - 4s 337ms/step - loss: 0.1288 - sparse_categorical_crossentropy: 0.0664 - sparse_categorical_accuracy: 0.9756 - scaled_adversarial_loss: 0.0624 - val_loss: 0.1725 - val_sparse_categorical_crossentropy: 0.1042 - val_sparse_categorical_accuracy: 0.9599 - val_scaled_adversarial_loss: 0.0683\n",
      "Epoch 852/1000\n",
      "11/11 [==============================] - 4s 337ms/step - loss: 0.1286 - sparse_categorical_crossentropy: 0.0675 - sparse_categorical_accuracy: 0.9775 - scaled_adversarial_loss: 0.0611 - val_loss: 0.1822 - val_sparse_categorical_crossentropy: 0.1066 - val_sparse_categorical_accuracy: 0.9599 - val_scaled_adversarial_loss: 0.0756\n",
      "Epoch 853/1000\n",
      "11/11 [==============================] - 4s 336ms/step - loss: 0.1286 - sparse_categorical_crossentropy: 0.0644 - sparse_categorical_accuracy: 0.9777 - scaled_adversarial_loss: 0.0642 - val_loss: 0.1888 - val_sparse_categorical_crossentropy: 0.1098 - val_sparse_categorical_accuracy: 0.9599 - val_scaled_adversarial_loss: 0.0790\n",
      "Epoch 854/1000\n",
      "11/11 [==============================] - 4s 336ms/step - loss: 0.1221 - sparse_categorical_crossentropy: 0.0610 - sparse_categorical_accuracy: 0.9788 - scaled_adversarial_loss: 0.0610 - val_loss: 0.1917 - val_sparse_categorical_crossentropy: 0.1091 - val_sparse_categorical_accuracy: 0.9636 - val_scaled_adversarial_loss: 0.0827\n",
      "Epoch 855/1000\n",
      "11/11 [==============================] - 4s 335ms/step - loss: 0.1286 - sparse_categorical_crossentropy: 0.0662 - sparse_categorical_accuracy: 0.9764 - scaled_adversarial_loss: 0.0624 - val_loss: 0.1964 - val_sparse_categorical_crossentropy: 0.1167 - val_sparse_categorical_accuracy: 0.9569 - val_scaled_adversarial_loss: 0.0797\n",
      "Epoch 856/1000\n",
      "11/11 [==============================] - 4s 337ms/step - loss: 0.1334 - sparse_categorical_crossentropy: 0.0702 - sparse_categorical_accuracy: 0.9749 - scaled_adversarial_loss: 0.0632 - val_loss: 0.1757 - val_sparse_categorical_crossentropy: 0.1021 - val_sparse_categorical_accuracy: 0.9613 - val_scaled_adversarial_loss: 0.0736\n",
      "Epoch 857/1000\n",
      "11/11 [==============================] - 4s 336ms/step - loss: 0.1238 - sparse_categorical_crossentropy: 0.0616 - sparse_categorical_accuracy: 0.9794 - scaled_adversarial_loss: 0.0622 - val_loss: 0.1839 - val_sparse_categorical_crossentropy: 0.1108 - val_sparse_categorical_accuracy: 0.9576 - val_scaled_adversarial_loss: 0.0731\n",
      "Epoch 858/1000\n",
      "11/11 [==============================] - 4s 335ms/step - loss: 0.1260 - sparse_categorical_crossentropy: 0.0646 - sparse_categorical_accuracy: 0.9777 - scaled_adversarial_loss: 0.0614 - val_loss: 0.1771 - val_sparse_categorical_crossentropy: 0.1070 - val_sparse_categorical_accuracy: 0.9584 - val_scaled_adversarial_loss: 0.0701\n",
      "Epoch 859/1000\n",
      "11/11 [==============================] - 4s 344ms/step - loss: 0.1260 - sparse_categorical_crossentropy: 0.0645 - sparse_categorical_accuracy: 0.9777 - scaled_adversarial_loss: 0.0615 - val_loss: 0.1764 - val_sparse_categorical_crossentropy: 0.1043 - val_sparse_categorical_accuracy: 0.9584 - val_scaled_adversarial_loss: 0.0721\n",
      "Epoch 860/1000\n",
      "11/11 [==============================] - 4s 335ms/step - loss: 0.1292 - sparse_categorical_crossentropy: 0.0697 - sparse_categorical_accuracy: 0.9790 - scaled_adversarial_loss: 0.0595 - val_loss: 0.1774 - val_sparse_categorical_crossentropy: 0.1019 - val_sparse_categorical_accuracy: 0.9599 - val_scaled_adversarial_loss: 0.0755\n",
      "Epoch 861/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.1212 - sparse_categorical_crossentropy: 0.0580 - sparse_categorical_accuracy: 0.9810 - scaled_adversarial_loss: 0.0632 - val_loss: 0.1850 - val_sparse_categorical_crossentropy: 0.1140 - val_sparse_categorical_accuracy: 0.9599 - val_scaled_adversarial_loss: 0.0711\n",
      "Epoch 862/1000\n",
      "11/11 [==============================] - 4s 336ms/step - loss: 0.1306 - sparse_categorical_crossentropy: 0.0682 - sparse_categorical_accuracy: 0.9768 - scaled_adversarial_loss: 0.0624 - val_loss: 0.1731 - val_sparse_categorical_crossentropy: 0.0999 - val_sparse_categorical_accuracy: 0.9591 - val_scaled_adversarial_loss: 0.0732\n",
      "Epoch 863/1000\n",
      "11/11 [==============================] - 4s 338ms/step - loss: 0.1260 - sparse_categorical_crossentropy: 0.0633 - sparse_categorical_accuracy: 0.9769 - scaled_adversarial_loss: 0.0628 - val_loss: 0.1849 - val_sparse_categorical_crossentropy: 0.1116 - val_sparse_categorical_accuracy: 0.9576 - val_scaled_adversarial_loss: 0.0733\n",
      "Epoch 864/1000\n",
      "11/11 [==============================] - 4s 336ms/step - loss: 0.1300 - sparse_categorical_crossentropy: 0.0663 - sparse_categorical_accuracy: 0.9764 - scaled_adversarial_loss: 0.0637 - val_loss: 0.1888 - val_sparse_categorical_crossentropy: 0.1092 - val_sparse_categorical_accuracy: 0.9636 - val_scaled_adversarial_loss: 0.0797\n",
      "Epoch 865/1000\n",
      "11/11 [==============================] - 4s 338ms/step - loss: 0.1194 - sparse_categorical_crossentropy: 0.0592 - sparse_categorical_accuracy: 0.9792 - scaled_adversarial_loss: 0.0603 - val_loss: 0.1704 - val_sparse_categorical_crossentropy: 0.1021 - val_sparse_categorical_accuracy: 0.9591 - val_scaled_adversarial_loss: 0.0683\n",
      "Epoch 866/1000\n",
      "11/11 [==============================] - 4s 336ms/step - loss: 0.1225 - sparse_categorical_crossentropy: 0.0609 - sparse_categorical_accuracy: 0.9768 - scaled_adversarial_loss: 0.0616 - val_loss: 0.1615 - val_sparse_categorical_crossentropy: 0.0940 - val_sparse_categorical_accuracy: 0.9651 - val_scaled_adversarial_loss: 0.0675\n",
      "Epoch 867/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.1268 - sparse_categorical_crossentropy: 0.0640 - sparse_categorical_accuracy: 0.9790 - scaled_adversarial_loss: 0.0629 - val_loss: 0.1714 - val_sparse_categorical_crossentropy: 0.1048 - val_sparse_categorical_accuracy: 0.9576 - val_scaled_adversarial_loss: 0.0666\n",
      "Epoch 868/1000\n",
      "11/11 [==============================] - 4s 335ms/step - loss: 0.1225 - sparse_categorical_crossentropy: 0.0607 - sparse_categorical_accuracy: 0.9799 - scaled_adversarial_loss: 0.0618 - val_loss: 0.1735 - val_sparse_categorical_crossentropy: 0.0981 - val_sparse_categorical_accuracy: 0.9643 - val_scaled_adversarial_loss: 0.0753\n",
      "Epoch 869/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.1255 - sparse_categorical_crossentropy: 0.0610 - sparse_categorical_accuracy: 0.9801 - scaled_adversarial_loss: 0.0645 - val_loss: 0.1861 - val_sparse_categorical_crossentropy: 0.1116 - val_sparse_categorical_accuracy: 0.9621 - val_scaled_adversarial_loss: 0.0745\n",
      "Epoch 870/1000\n",
      "11/11 [==============================] - 4s 338ms/step - loss: 0.1188 - sparse_categorical_crossentropy: 0.0589 - sparse_categorical_accuracy: 0.9795 - scaled_adversarial_loss: 0.0599 - val_loss: 0.1876 - val_sparse_categorical_crossentropy: 0.1055 - val_sparse_categorical_accuracy: 0.9576 - val_scaled_adversarial_loss: 0.0821\n",
      "Epoch 871/1000\n",
      "11/11 [==============================] - 4s 335ms/step - loss: 0.1316 - sparse_categorical_crossentropy: 0.0696 - sparse_categorical_accuracy: 0.9773 - scaled_adversarial_loss: 0.0620 - val_loss: 0.1822 - val_sparse_categorical_crossentropy: 0.1019 - val_sparse_categorical_accuracy: 0.9621 - val_scaled_adversarial_loss: 0.0803\n",
      "Epoch 872/1000\n",
      "11/11 [==============================] - 4s 339ms/step - loss: 0.1292 - sparse_categorical_crossentropy: 0.0666 - sparse_categorical_accuracy: 0.9775 - scaled_adversarial_loss: 0.0626 - val_loss: 0.1928 - val_sparse_categorical_crossentropy: 0.1107 - val_sparse_categorical_accuracy: 0.9628 - val_scaled_adversarial_loss: 0.0821\n",
      "Epoch 873/1000\n",
      "11/11 [==============================] - 4s 342ms/step - loss: 0.1222 - sparse_categorical_crossentropy: 0.0613 - sparse_categorical_accuracy: 0.9781 - scaled_adversarial_loss: 0.0610 - val_loss: 0.1930 - val_sparse_categorical_crossentropy: 0.1109 - val_sparse_categorical_accuracy: 0.9651 - val_scaled_adversarial_loss: 0.0821\n",
      "Epoch 874/1000\n",
      "11/11 [==============================] - 4s 339ms/step - loss: 0.1241 - sparse_categorical_crossentropy: 0.0590 - sparse_categorical_accuracy: 0.9786 - scaled_adversarial_loss: 0.0651 - val_loss: 0.1901 - val_sparse_categorical_crossentropy: 0.1103 - val_sparse_categorical_accuracy: 0.9628 - val_scaled_adversarial_loss: 0.0798\n",
      "Epoch 875/1000\n",
      "11/11 [==============================] - 4s 342ms/step - loss: 0.1303 - sparse_categorical_crossentropy: 0.0639 - sparse_categorical_accuracy: 0.9788 - scaled_adversarial_loss: 0.0663 - val_loss: 0.1850 - val_sparse_categorical_crossentropy: 0.1067 - val_sparse_categorical_accuracy: 0.9584 - val_scaled_adversarial_loss: 0.0783\n",
      "Epoch 876/1000\n",
      "11/11 [==============================] - 4s 335ms/step - loss: 0.1246 - sparse_categorical_crossentropy: 0.0638 - sparse_categorical_accuracy: 0.9786 - scaled_adversarial_loss: 0.0608 - val_loss: 0.1660 - val_sparse_categorical_crossentropy: 0.0942 - val_sparse_categorical_accuracy: 0.9621 - val_scaled_adversarial_loss: 0.0717\n",
      "Epoch 877/1000\n",
      "11/11 [==============================] - 4s 344ms/step - loss: 0.1230 - sparse_categorical_crossentropy: 0.0601 - sparse_categorical_accuracy: 0.9803 - scaled_adversarial_loss: 0.0630 - val_loss: 0.1820 - val_sparse_categorical_crossentropy: 0.1046 - val_sparse_categorical_accuracy: 0.9606 - val_scaled_adversarial_loss: 0.0773\n",
      "Epoch 878/1000\n",
      "11/11 [==============================] - 4s 336ms/step - loss: 0.1242 - sparse_categorical_crossentropy: 0.0637 - sparse_categorical_accuracy: 0.9795 - scaled_adversarial_loss: 0.0605 - val_loss: 0.2014 - val_sparse_categorical_crossentropy: 0.1128 - val_sparse_categorical_accuracy: 0.9576 - val_scaled_adversarial_loss: 0.0886\n",
      "Epoch 879/1000\n",
      "11/11 [==============================] - 4s 336ms/step - loss: 0.1291 - sparse_categorical_crossentropy: 0.0637 - sparse_categorical_accuracy: 0.9784 - scaled_adversarial_loss: 0.0655 - val_loss: 0.1784 - val_sparse_categorical_crossentropy: 0.1082 - val_sparse_categorical_accuracy: 0.9621 - val_scaled_adversarial_loss: 0.0702\n",
      "Epoch 880/1000\n",
      "11/11 [==============================] - 4s 335ms/step - loss: 0.1268 - sparse_categorical_crossentropy: 0.0627 - sparse_categorical_accuracy: 0.9795 - scaled_adversarial_loss: 0.0642 - val_loss: 0.1714 - val_sparse_categorical_crossentropy: 0.0973 - val_sparse_categorical_accuracy: 0.9613 - val_scaled_adversarial_loss: 0.0742\n",
      "Epoch 881/1000\n",
      "11/11 [==============================] - 4s 335ms/step - loss: 0.1247 - sparse_categorical_crossentropy: 0.0641 - sparse_categorical_accuracy: 0.9781 - scaled_adversarial_loss: 0.0607 - val_loss: 0.1749 - val_sparse_categorical_crossentropy: 0.1011 - val_sparse_categorical_accuracy: 0.9628 - val_scaled_adversarial_loss: 0.0739\n",
      "Epoch 882/1000\n",
      "11/11 [==============================] - 4s 337ms/step - loss: 0.1183 - sparse_categorical_crossentropy: 0.0577 - sparse_categorical_accuracy: 0.9799 - scaled_adversarial_loss: 0.0606 - val_loss: 0.1777 - val_sparse_categorical_crossentropy: 0.1013 - val_sparse_categorical_accuracy: 0.9599 - val_scaled_adversarial_loss: 0.0764\n",
      "Epoch 883/1000\n",
      "11/11 [==============================] - 4s 335ms/step - loss: 0.1255 - sparse_categorical_crossentropy: 0.0596 - sparse_categorical_accuracy: 0.9795 - scaled_adversarial_loss: 0.0659 - val_loss: 0.1819 - val_sparse_categorical_crossentropy: 0.1064 - val_sparse_categorical_accuracy: 0.9613 - val_scaled_adversarial_loss: 0.0755\n",
      "Epoch 884/1000\n",
      "11/11 [==============================] - 4s 338ms/step - loss: 0.1273 - sparse_categorical_crossentropy: 0.0649 - sparse_categorical_accuracy: 0.9782 - scaled_adversarial_loss: 0.0624 - val_loss: 0.1774 - val_sparse_categorical_crossentropy: 0.1011 - val_sparse_categorical_accuracy: 0.9606 - val_scaled_adversarial_loss: 0.0763\n",
      "Epoch 885/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.1294 - sparse_categorical_crossentropy: 0.0666 - sparse_categorical_accuracy: 0.9753 - scaled_adversarial_loss: 0.0628 - val_loss: 0.1725 - val_sparse_categorical_crossentropy: 0.0984 - val_sparse_categorical_accuracy: 0.9613 - val_scaled_adversarial_loss: 0.0741\n",
      "Epoch 886/1000\n",
      "11/11 [==============================] - 4s 330ms/step - loss: 0.1260 - sparse_categorical_crossentropy: 0.0637 - sparse_categorical_accuracy: 0.9790 - scaled_adversarial_loss: 0.0622 - val_loss: 0.1650 - val_sparse_categorical_crossentropy: 0.0974 - val_sparse_categorical_accuracy: 0.9613 - val_scaled_adversarial_loss: 0.0677\n",
      "Epoch 887/1000\n",
      "11/11 [==============================] - 4s 336ms/step - loss: 0.1241 - sparse_categorical_crossentropy: 0.0641 - sparse_categorical_accuracy: 0.9777 - scaled_adversarial_loss: 0.0600 - val_loss: 0.1828 - val_sparse_categorical_crossentropy: 0.1095 - val_sparse_categorical_accuracy: 0.9599 - val_scaled_adversarial_loss: 0.0733\n",
      "Epoch 888/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.1310 - sparse_categorical_crossentropy: 0.0689 - sparse_categorical_accuracy: 0.9747 - scaled_adversarial_loss: 0.0621 - val_loss: 0.1703 - val_sparse_categorical_crossentropy: 0.1009 - val_sparse_categorical_accuracy: 0.9599 - val_scaled_adversarial_loss: 0.0694\n",
      "Epoch 889/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.1248 - sparse_categorical_crossentropy: 0.0611 - sparse_categorical_accuracy: 0.9801 - scaled_adversarial_loss: 0.0638 - val_loss: 0.1860 - val_sparse_categorical_crossentropy: 0.1130 - val_sparse_categorical_accuracy: 0.9584 - val_scaled_adversarial_loss: 0.0731\n",
      "Epoch 890/1000\n",
      "11/11 [==============================] - 4s 337ms/step - loss: 0.1331 - sparse_categorical_crossentropy: 0.0676 - sparse_categorical_accuracy: 0.9747 - scaled_adversarial_loss: 0.0655 - val_loss: 0.1707 - val_sparse_categorical_crossentropy: 0.0953 - val_sparse_categorical_accuracy: 0.9606 - val_scaled_adversarial_loss: 0.0754\n",
      "Epoch 891/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.1318 - sparse_categorical_crossentropy: 0.0672 - sparse_categorical_accuracy: 0.9740 - scaled_adversarial_loss: 0.0646 - val_loss: 0.1811 - val_sparse_categorical_crossentropy: 0.1065 - val_sparse_categorical_accuracy: 0.9561 - val_scaled_adversarial_loss: 0.0745\n",
      "Epoch 892/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.1258 - sparse_categorical_crossentropy: 0.0639 - sparse_categorical_accuracy: 0.9773 - scaled_adversarial_loss: 0.0618 - val_loss: 0.1740 - val_sparse_categorical_crossentropy: 0.0993 - val_sparse_categorical_accuracy: 0.9599 - val_scaled_adversarial_loss: 0.0747\n",
      "Epoch 893/1000\n",
      "11/11 [==============================] - 4s 335ms/step - loss: 0.1325 - sparse_categorical_crossentropy: 0.0679 - sparse_categorical_accuracy: 0.9760 - scaled_adversarial_loss: 0.0645 - val_loss: 0.1742 - val_sparse_categorical_crossentropy: 0.1017 - val_sparse_categorical_accuracy: 0.9606 - val_scaled_adversarial_loss: 0.0725\n",
      "Epoch 894/1000\n",
      "11/11 [==============================] - 4s 335ms/step - loss: 0.1245 - sparse_categorical_crossentropy: 0.0606 - sparse_categorical_accuracy: 0.9777 - scaled_adversarial_loss: 0.0639 - val_loss: 0.1873 - val_sparse_categorical_crossentropy: 0.1079 - val_sparse_categorical_accuracy: 0.9621 - val_scaled_adversarial_loss: 0.0794\n",
      "Epoch 895/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.1244 - sparse_categorical_crossentropy: 0.0606 - sparse_categorical_accuracy: 0.9794 - scaled_adversarial_loss: 0.0638 - val_loss: 0.1700 - val_sparse_categorical_crossentropy: 0.0959 - val_sparse_categorical_accuracy: 0.9636 - val_scaled_adversarial_loss: 0.0741\n",
      "Epoch 896/1000\n",
      "11/11 [==============================] - 4s 337ms/step - loss: 0.1235 - sparse_categorical_crossentropy: 0.0619 - sparse_categorical_accuracy: 0.9788 - scaled_adversarial_loss: 0.0616 - val_loss: 0.1829 - val_sparse_categorical_crossentropy: 0.1079 - val_sparse_categorical_accuracy: 0.9628 - val_scaled_adversarial_loss: 0.0750\n",
      "Epoch 897/1000\n",
      "11/11 [==============================] - 4s 337ms/step - loss: 0.1310 - sparse_categorical_crossentropy: 0.0638 - sparse_categorical_accuracy: 0.9782 - scaled_adversarial_loss: 0.0673 - val_loss: 0.1626 - val_sparse_categorical_crossentropy: 0.0997 - val_sparse_categorical_accuracy: 0.9546 - val_scaled_adversarial_loss: 0.0629\n",
      "Epoch 898/1000\n",
      "11/11 [==============================] - 4s 337ms/step - loss: 0.1281 - sparse_categorical_crossentropy: 0.0649 - sparse_categorical_accuracy: 0.9775 - scaled_adversarial_loss: 0.0632 - val_loss: 0.1689 - val_sparse_categorical_crossentropy: 0.0935 - val_sparse_categorical_accuracy: 0.9606 - val_scaled_adversarial_loss: 0.0754\n",
      "Epoch 899/1000\n",
      "11/11 [==============================] - 4s 337ms/step - loss: 0.1235 - sparse_categorical_crossentropy: 0.0641 - sparse_categorical_accuracy: 0.9775 - scaled_adversarial_loss: 0.0594 - val_loss: 0.1596 - val_sparse_categorical_crossentropy: 0.0942 - val_sparse_categorical_accuracy: 0.9643 - val_scaled_adversarial_loss: 0.0654\n",
      "Epoch 900/1000\n",
      "11/11 [==============================] - 4s 336ms/step - loss: 0.1153 - sparse_categorical_crossentropy: 0.0557 - sparse_categorical_accuracy: 0.9820 - scaled_adversarial_loss: 0.0596 - val_loss: 0.1721 - val_sparse_categorical_crossentropy: 0.1008 - val_sparse_categorical_accuracy: 0.9636 - val_scaled_adversarial_loss: 0.0713\n",
      "Epoch 901/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.1228 - sparse_categorical_crossentropy: 0.0634 - sparse_categorical_accuracy: 0.9781 - scaled_adversarial_loss: 0.0594 - val_loss: 0.1856 - val_sparse_categorical_crossentropy: 0.1043 - val_sparse_categorical_accuracy: 0.9621 - val_scaled_adversarial_loss: 0.0814\n",
      "Epoch 902/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.1263 - sparse_categorical_crossentropy: 0.0633 - sparse_categorical_accuracy: 0.9762 - scaled_adversarial_loss: 0.0630 - val_loss: 0.1763 - val_sparse_categorical_crossentropy: 0.1074 - val_sparse_categorical_accuracy: 0.9584 - val_scaled_adversarial_loss: 0.0690\n",
      "Epoch 903/1000\n",
      "11/11 [==============================] - 4s 338ms/step - loss: 0.1227 - sparse_categorical_crossentropy: 0.0620 - sparse_categorical_accuracy: 0.9762 - scaled_adversarial_loss: 0.0607 - val_loss: 0.1803 - val_sparse_categorical_crossentropy: 0.1071 - val_sparse_categorical_accuracy: 0.9606 - val_scaled_adversarial_loss: 0.0731\n",
      "Epoch 904/1000\n",
      "11/11 [==============================] - 4s 344ms/step - loss: 0.1270 - sparse_categorical_crossentropy: 0.0640 - sparse_categorical_accuracy: 0.9769 - scaled_adversarial_loss: 0.0630 - val_loss: 0.1786 - val_sparse_categorical_crossentropy: 0.1019 - val_sparse_categorical_accuracy: 0.9606 - val_scaled_adversarial_loss: 0.0768\n",
      "Epoch 905/1000\n",
      "11/11 [==============================] - 4s 327ms/step - loss: 0.1222 - sparse_categorical_crossentropy: 0.0617 - sparse_categorical_accuracy: 0.9803 - scaled_adversarial_loss: 0.0605 - val_loss: 0.1873 - val_sparse_categorical_crossentropy: 0.1086 - val_sparse_categorical_accuracy: 0.9606 - val_scaled_adversarial_loss: 0.0787\n",
      "Epoch 906/1000\n",
      "11/11 [==============================] - 4s 327ms/step - loss: 0.1277 - sparse_categorical_crossentropy: 0.0661 - sparse_categorical_accuracy: 0.9771 - scaled_adversarial_loss: 0.0616 - val_loss: 0.1739 - val_sparse_categorical_crossentropy: 0.1052 - val_sparse_categorical_accuracy: 0.9613 - val_scaled_adversarial_loss: 0.0688\n",
      "Epoch 907/1000\n",
      "11/11 [==============================] - 4s 329ms/step - loss: 0.1250 - sparse_categorical_crossentropy: 0.0647 - sparse_categorical_accuracy: 0.9777 - scaled_adversarial_loss: 0.0602 - val_loss: 0.1678 - val_sparse_categorical_crossentropy: 0.1010 - val_sparse_categorical_accuracy: 0.9591 - val_scaled_adversarial_loss: 0.0668\n",
      "Epoch 908/1000\n",
      "11/11 [==============================] - 4s 329ms/step - loss: 0.1249 - sparse_categorical_crossentropy: 0.0632 - sparse_categorical_accuracy: 0.9807 - scaled_adversarial_loss: 0.0617 - val_loss: 0.1651 - val_sparse_categorical_crossentropy: 0.1039 - val_sparse_categorical_accuracy: 0.9599 - val_scaled_adversarial_loss: 0.0612\n",
      "Epoch 909/1000\n",
      "11/11 [==============================] - 4s 329ms/step - loss: 0.1242 - sparse_categorical_crossentropy: 0.0638 - sparse_categorical_accuracy: 0.9782 - scaled_adversarial_loss: 0.0604 - val_loss: 0.1681 - val_sparse_categorical_crossentropy: 0.0996 - val_sparse_categorical_accuracy: 0.9628 - val_scaled_adversarial_loss: 0.0686\n",
      "Epoch 910/1000\n",
      "11/11 [==============================] - 4s 330ms/step - loss: 0.1271 - sparse_categorical_crossentropy: 0.0635 - sparse_categorical_accuracy: 0.9797 - scaled_adversarial_loss: 0.0637 - val_loss: 0.1747 - val_sparse_categorical_crossentropy: 0.1026 - val_sparse_categorical_accuracy: 0.9643 - val_scaled_adversarial_loss: 0.0721\n",
      "Epoch 911/1000\n",
      "11/11 [==============================] - 4s 326ms/step - loss: 0.1223 - sparse_categorical_crossentropy: 0.0611 - sparse_categorical_accuracy: 0.9786 - scaled_adversarial_loss: 0.0612 - val_loss: 0.1674 - val_sparse_categorical_crossentropy: 0.0974 - val_sparse_categorical_accuracy: 0.9636 - val_scaled_adversarial_loss: 0.0700\n",
      "Epoch 912/1000\n",
      "11/11 [==============================] - 4s 330ms/step - loss: 0.1239 - sparse_categorical_crossentropy: 0.0616 - sparse_categorical_accuracy: 0.9801 - scaled_adversarial_loss: 0.0623 - val_loss: 0.1725 - val_sparse_categorical_crossentropy: 0.1039 - val_sparse_categorical_accuracy: 0.9621 - val_scaled_adversarial_loss: 0.0686\n",
      "Epoch 913/1000\n",
      "11/11 [==============================] - 4s 327ms/step - loss: 0.1200 - sparse_categorical_crossentropy: 0.0595 - sparse_categorical_accuracy: 0.9812 - scaled_adversarial_loss: 0.0604 - val_loss: 0.1768 - val_sparse_categorical_crossentropy: 0.1056 - val_sparse_categorical_accuracy: 0.9621 - val_scaled_adversarial_loss: 0.0712\n",
      "Epoch 914/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.1219 - sparse_categorical_crossentropy: 0.0620 - sparse_categorical_accuracy: 0.9794 - scaled_adversarial_loss: 0.0599 - val_loss: 0.1651 - val_sparse_categorical_crossentropy: 0.0996 - val_sparse_categorical_accuracy: 0.9651 - val_scaled_adversarial_loss: 0.0655\n",
      "Epoch 915/1000\n",
      "11/11 [==============================] - 4s 331ms/step - loss: 0.1208 - sparse_categorical_crossentropy: 0.0572 - sparse_categorical_accuracy: 0.9797 - scaled_adversarial_loss: 0.0636 - val_loss: 0.1680 - val_sparse_categorical_crossentropy: 0.1031 - val_sparse_categorical_accuracy: 0.9621 - val_scaled_adversarial_loss: 0.0649\n",
      "Epoch 916/1000\n",
      "11/11 [==============================] - 4s 329ms/step - loss: 0.1211 - sparse_categorical_crossentropy: 0.0618 - sparse_categorical_accuracy: 0.9768 - scaled_adversarial_loss: 0.0593 - val_loss: 0.1931 - val_sparse_categorical_crossentropy: 0.1124 - val_sparse_categorical_accuracy: 0.9606 - val_scaled_adversarial_loss: 0.0807\n",
      "Epoch 917/1000\n",
      "11/11 [==============================] - 4s 331ms/step - loss: 0.1239 - sparse_categorical_crossentropy: 0.0620 - sparse_categorical_accuracy: 0.9794 - scaled_adversarial_loss: 0.0619 - val_loss: 0.1767 - val_sparse_categorical_crossentropy: 0.1042 - val_sparse_categorical_accuracy: 0.9584 - val_scaled_adversarial_loss: 0.0725\n",
      "Epoch 918/1000\n",
      "11/11 [==============================] - 4s 330ms/step - loss: 0.1322 - sparse_categorical_crossentropy: 0.0686 - sparse_categorical_accuracy: 0.9751 - scaled_adversarial_loss: 0.0636 - val_loss: 0.1686 - val_sparse_categorical_crossentropy: 0.1003 - val_sparse_categorical_accuracy: 0.9628 - val_scaled_adversarial_loss: 0.0683\n",
      "Epoch 919/1000\n",
      "11/11 [==============================] - 4s 331ms/step - loss: 0.1188 - sparse_categorical_crossentropy: 0.0571 - sparse_categorical_accuracy: 0.9805 - scaled_adversarial_loss: 0.0617 - val_loss: 0.1794 - val_sparse_categorical_crossentropy: 0.1079 - val_sparse_categorical_accuracy: 0.9621 - val_scaled_adversarial_loss: 0.0715\n",
      "Epoch 920/1000\n",
      "11/11 [==============================] - 4s 330ms/step - loss: 0.1203 - sparse_categorical_crossentropy: 0.0611 - sparse_categorical_accuracy: 0.9781 - scaled_adversarial_loss: 0.0592 - val_loss: 0.1779 - val_sparse_categorical_crossentropy: 0.1005 - val_sparse_categorical_accuracy: 0.9643 - val_scaled_adversarial_loss: 0.0774\n",
      "Epoch 921/1000\n",
      "11/11 [==============================] - 4s 328ms/step - loss: 0.1252 - sparse_categorical_crossentropy: 0.0636 - sparse_categorical_accuracy: 0.9779 - scaled_adversarial_loss: 0.0617 - val_loss: 0.1824 - val_sparse_categorical_crossentropy: 0.1122 - val_sparse_categorical_accuracy: 0.9569 - val_scaled_adversarial_loss: 0.0702\n",
      "Epoch 922/1000\n",
      "11/11 [==============================] - 4s 328ms/step - loss: 0.1190 - sparse_categorical_crossentropy: 0.0562 - sparse_categorical_accuracy: 0.9827 - scaled_adversarial_loss: 0.0628 - val_loss: 0.1724 - val_sparse_categorical_crossentropy: 0.1053 - val_sparse_categorical_accuracy: 0.9599 - val_scaled_adversarial_loss: 0.0671\n",
      "Epoch 923/1000\n",
      "11/11 [==============================] - 4s 330ms/step - loss: 0.1215 - sparse_categorical_crossentropy: 0.0617 - sparse_categorical_accuracy: 0.9766 - scaled_adversarial_loss: 0.0599 - val_loss: 0.1839 - val_sparse_categorical_crossentropy: 0.1070 - val_sparse_categorical_accuracy: 0.9613 - val_scaled_adversarial_loss: 0.0769\n",
      "Epoch 924/1000\n",
      "11/11 [==============================] - 4s 329ms/step - loss: 0.1197 - sparse_categorical_crossentropy: 0.0568 - sparse_categorical_accuracy: 0.9829 - scaled_adversarial_loss: 0.0630 - val_loss: 0.1907 - val_sparse_categorical_crossentropy: 0.1120 - val_sparse_categorical_accuracy: 0.9606 - val_scaled_adversarial_loss: 0.0787\n",
      "Epoch 925/1000\n",
      "11/11 [==============================] - 4s 329ms/step - loss: 0.1240 - sparse_categorical_crossentropy: 0.0613 - sparse_categorical_accuracy: 0.9794 - scaled_adversarial_loss: 0.0627 - val_loss: 0.1815 - val_sparse_categorical_crossentropy: 0.1052 - val_sparse_categorical_accuracy: 0.9651 - val_scaled_adversarial_loss: 0.0763\n",
      "Epoch 926/1000\n",
      "11/11 [==============================] - 4s 327ms/step - loss: 0.1282 - sparse_categorical_crossentropy: 0.0634 - sparse_categorical_accuracy: 0.9786 - scaled_adversarial_loss: 0.0648 - val_loss: 0.1714 - val_sparse_categorical_crossentropy: 0.0999 - val_sparse_categorical_accuracy: 0.9628 - val_scaled_adversarial_loss: 0.0715\n",
      "Epoch 927/1000\n",
      "11/11 [==============================] - 4s 330ms/step - loss: 0.1182 - sparse_categorical_crossentropy: 0.0591 - sparse_categorical_accuracy: 0.9797 - scaled_adversarial_loss: 0.0591 - val_loss: 0.1710 - val_sparse_categorical_crossentropy: 0.1027 - val_sparse_categorical_accuracy: 0.9621 - val_scaled_adversarial_loss: 0.0683\n",
      "Epoch 928/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.1220 - sparse_categorical_crossentropy: 0.0630 - sparse_categorical_accuracy: 0.9797 - scaled_adversarial_loss: 0.0590 - val_loss: 0.1792 - val_sparse_categorical_crossentropy: 0.1035 - val_sparse_categorical_accuracy: 0.9673 - val_scaled_adversarial_loss: 0.0758\n",
      "Epoch 929/1000\n",
      "11/11 [==============================] - 4s 329ms/step - loss: 0.1221 - sparse_categorical_crossentropy: 0.0604 - sparse_categorical_accuracy: 0.9792 - scaled_adversarial_loss: 0.0617 - val_loss: 0.1729 - val_sparse_categorical_crossentropy: 0.1001 - val_sparse_categorical_accuracy: 0.9651 - val_scaled_adversarial_loss: 0.0728\n",
      "Epoch 930/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.1230 - sparse_categorical_crossentropy: 0.0613 - sparse_categorical_accuracy: 0.9786 - scaled_adversarial_loss: 0.0618 - val_loss: 0.1803 - val_sparse_categorical_crossentropy: 0.1075 - val_sparse_categorical_accuracy: 0.9636 - val_scaled_adversarial_loss: 0.0728\n",
      "Epoch 931/1000\n",
      "11/11 [==============================] - 4s 336ms/step - loss: 0.1292 - sparse_categorical_crossentropy: 0.0677 - sparse_categorical_accuracy: 0.9766 - scaled_adversarial_loss: 0.0615 - val_loss: 0.1714 - val_sparse_categorical_crossentropy: 0.1006 - val_sparse_categorical_accuracy: 0.9606 - val_scaled_adversarial_loss: 0.0708\n",
      "Epoch 932/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.1225 - sparse_categorical_crossentropy: 0.0600 - sparse_categorical_accuracy: 0.9808 - scaled_adversarial_loss: 0.0624 - val_loss: 0.1889 - val_sparse_categorical_crossentropy: 0.1090 - val_sparse_categorical_accuracy: 0.9636 - val_scaled_adversarial_loss: 0.0799\n",
      "Epoch 933/1000\n",
      "11/11 [==============================] - 4s 339ms/step - loss: 0.1236 - sparse_categorical_crossentropy: 0.0607 - sparse_categorical_accuracy: 0.9794 - scaled_adversarial_loss: 0.0629 - val_loss: 0.1713 - val_sparse_categorical_crossentropy: 0.0966 - val_sparse_categorical_accuracy: 0.9636 - val_scaled_adversarial_loss: 0.0748\n",
      "Epoch 934/1000\n",
      "11/11 [==============================] - 4s 342ms/step - loss: 0.1235 - sparse_categorical_crossentropy: 0.0643 - sparse_categorical_accuracy: 0.9781 - scaled_adversarial_loss: 0.0592 - val_loss: 0.1672 - val_sparse_categorical_crossentropy: 0.0961 - val_sparse_categorical_accuracy: 0.9643 - val_scaled_adversarial_loss: 0.0711\n",
      "Epoch 935/1000\n",
      "11/11 [==============================] - 4s 341ms/step - loss: 0.1266 - sparse_categorical_crossentropy: 0.0636 - sparse_categorical_accuracy: 0.9775 - scaled_adversarial_loss: 0.0630 - val_loss: 0.1740 - val_sparse_categorical_crossentropy: 0.1032 - val_sparse_categorical_accuracy: 0.9643 - val_scaled_adversarial_loss: 0.0707\n",
      "Epoch 936/1000\n",
      "11/11 [==============================] - 4s 330ms/step - loss: 0.1225 - sparse_categorical_crossentropy: 0.0628 - sparse_categorical_accuracy: 0.9790 - scaled_adversarial_loss: 0.0597 - val_loss: 0.1743 - val_sparse_categorical_crossentropy: 0.1007 - val_sparse_categorical_accuracy: 0.9584 - val_scaled_adversarial_loss: 0.0736\n",
      "Epoch 937/1000\n",
      "11/11 [==============================] - 4s 332ms/step - loss: 0.1147 - sparse_categorical_crossentropy: 0.0568 - sparse_categorical_accuracy: 0.9786 - scaled_adversarial_loss: 0.0579 - val_loss: 0.1875 - val_sparse_categorical_crossentropy: 0.1123 - val_sparse_categorical_accuracy: 0.9606 - val_scaled_adversarial_loss: 0.0752\n",
      "Epoch 938/1000\n",
      "11/11 [==============================] - 4s 331ms/step - loss: 0.1251 - sparse_categorical_crossentropy: 0.0620 - sparse_categorical_accuracy: 0.9775 - scaled_adversarial_loss: 0.0631 - val_loss: 0.1763 - val_sparse_categorical_crossentropy: 0.1070 - val_sparse_categorical_accuracy: 0.9651 - val_scaled_adversarial_loss: 0.0692\n",
      "Epoch 939/1000\n",
      "11/11 [==============================] - 4s 328ms/step - loss: 0.1259 - sparse_categorical_crossentropy: 0.0652 - sparse_categorical_accuracy: 0.9758 - scaled_adversarial_loss: 0.0607 - val_loss: 0.1737 - val_sparse_categorical_crossentropy: 0.1011 - val_sparse_categorical_accuracy: 0.9621 - val_scaled_adversarial_loss: 0.0725\n",
      "Epoch 940/1000\n",
      "11/11 [==============================] - 4s 331ms/step - loss: 0.1184 - sparse_categorical_crossentropy: 0.0582 - sparse_categorical_accuracy: 0.9821 - scaled_adversarial_loss: 0.0601 - val_loss: 0.1660 - val_sparse_categorical_crossentropy: 0.0956 - val_sparse_categorical_accuracy: 0.9606 - val_scaled_adversarial_loss: 0.0704\n",
      "Epoch 941/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.1237 - sparse_categorical_crossentropy: 0.0617 - sparse_categorical_accuracy: 0.9779 - scaled_adversarial_loss: 0.0620 - val_loss: 0.1967 - val_sparse_categorical_crossentropy: 0.1105 - val_sparse_categorical_accuracy: 0.9584 - val_scaled_adversarial_loss: 0.0862\n",
      "Epoch 942/1000\n",
      "11/11 [==============================] - 4s 335ms/step - loss: 0.1254 - sparse_categorical_crossentropy: 0.0611 - sparse_categorical_accuracy: 0.9810 - scaled_adversarial_loss: 0.0643 - val_loss: 0.1904 - val_sparse_categorical_crossentropy: 0.1096 - val_sparse_categorical_accuracy: 0.9599 - val_scaled_adversarial_loss: 0.0807\n",
      "Epoch 943/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.1240 - sparse_categorical_crossentropy: 0.0597 - sparse_categorical_accuracy: 0.9766 - scaled_adversarial_loss: 0.0642 - val_loss: 0.1971 - val_sparse_categorical_crossentropy: 0.1138 - val_sparse_categorical_accuracy: 0.9584 - val_scaled_adversarial_loss: 0.0833\n",
      "Epoch 944/1000\n",
      "11/11 [==============================] - 4s 330ms/step - loss: 0.1239 - sparse_categorical_crossentropy: 0.0633 - sparse_categorical_accuracy: 0.9788 - scaled_adversarial_loss: 0.0606 - val_loss: 0.1773 - val_sparse_categorical_crossentropy: 0.1057 - val_sparse_categorical_accuracy: 0.9643 - val_scaled_adversarial_loss: 0.0717\n",
      "Epoch 945/1000\n",
      "11/11 [==============================] - 4s 331ms/step - loss: 0.1200 - sparse_categorical_crossentropy: 0.0583 - sparse_categorical_accuracy: 0.9790 - scaled_adversarial_loss: 0.0617 - val_loss: 0.1689 - val_sparse_categorical_crossentropy: 0.0981 - val_sparse_categorical_accuracy: 0.9628 - val_scaled_adversarial_loss: 0.0708\n",
      "Epoch 946/1000\n",
      "11/11 [==============================] - 4s 330ms/step - loss: 0.1200 - sparse_categorical_crossentropy: 0.0591 - sparse_categorical_accuracy: 0.9814 - scaled_adversarial_loss: 0.0610 - val_loss: 0.1710 - val_sparse_categorical_crossentropy: 0.0985 - val_sparse_categorical_accuracy: 0.9628 - val_scaled_adversarial_loss: 0.0725\n",
      "Epoch 947/1000\n",
      "11/11 [==============================] - 4s 335ms/step - loss: 0.1241 - sparse_categorical_crossentropy: 0.0613 - sparse_categorical_accuracy: 0.9784 - scaled_adversarial_loss: 0.0628 - val_loss: 0.1765 - val_sparse_categorical_crossentropy: 0.1048 - val_sparse_categorical_accuracy: 0.9628 - val_scaled_adversarial_loss: 0.0717\n",
      "Epoch 948/1000\n",
      "11/11 [==============================] - 4s 338ms/step - loss: 0.1218 - sparse_categorical_crossentropy: 0.0620 - sparse_categorical_accuracy: 0.9794 - scaled_adversarial_loss: 0.0597 - val_loss: 0.1876 - val_sparse_categorical_crossentropy: 0.1144 - val_sparse_categorical_accuracy: 0.9576 - val_scaled_adversarial_loss: 0.0733\n",
      "Epoch 949/1000\n",
      "11/11 [==============================] - 4s 330ms/step - loss: 0.1188 - sparse_categorical_crossentropy: 0.0563 - sparse_categorical_accuracy: 0.9794 - scaled_adversarial_loss: 0.0625 - val_loss: 0.1989 - val_sparse_categorical_crossentropy: 0.1149 - val_sparse_categorical_accuracy: 0.9584 - val_scaled_adversarial_loss: 0.0840\n",
      "Epoch 950/1000\n",
      "11/11 [==============================] - 4s 330ms/step - loss: 0.1221 - sparse_categorical_crossentropy: 0.0612 - sparse_categorical_accuracy: 0.9786 - scaled_adversarial_loss: 0.0609 - val_loss: 0.1868 - val_sparse_categorical_crossentropy: 0.1078 - val_sparse_categorical_accuracy: 0.9591 - val_scaled_adversarial_loss: 0.0790\n",
      "Epoch 951/1000\n",
      "11/11 [==============================] - 4s 330ms/step - loss: 0.1230 - sparse_categorical_crossentropy: 0.0626 - sparse_categorical_accuracy: 0.9769 - scaled_adversarial_loss: 0.0604 - val_loss: 0.1830 - val_sparse_categorical_crossentropy: 0.1097 - val_sparse_categorical_accuracy: 0.9613 - val_scaled_adversarial_loss: 0.0733\n",
      "Epoch 952/1000\n",
      "11/11 [==============================] - 4s 331ms/step - loss: 0.1260 - sparse_categorical_crossentropy: 0.0640 - sparse_categorical_accuracy: 0.9769 - scaled_adversarial_loss: 0.0620 - val_loss: 0.1844 - val_sparse_categorical_crossentropy: 0.1028 - val_sparse_categorical_accuracy: 0.9621 - val_scaled_adversarial_loss: 0.0816\n",
      "Epoch 953/1000\n",
      "11/11 [==============================] - 4s 335ms/step - loss: 0.1125 - sparse_categorical_crossentropy: 0.0506 - sparse_categorical_accuracy: 0.9825 - scaled_adversarial_loss: 0.0619 - val_loss: 0.1732 - val_sparse_categorical_crossentropy: 0.1005 - val_sparse_categorical_accuracy: 0.9613 - val_scaled_adversarial_loss: 0.0728\n",
      "Epoch 954/1000\n",
      "11/11 [==============================] - 4s 343ms/step - loss: 0.1197 - sparse_categorical_crossentropy: 0.0613 - sparse_categorical_accuracy: 0.9779 - scaled_adversarial_loss: 0.0583 - val_loss: 0.1704 - val_sparse_categorical_crossentropy: 0.0993 - val_sparse_categorical_accuracy: 0.9613 - val_scaled_adversarial_loss: 0.0712\n",
      "Epoch 955/1000\n",
      "11/11 [==============================] - 4s 331ms/step - loss: 0.1215 - sparse_categorical_crossentropy: 0.0599 - sparse_categorical_accuracy: 0.9794 - scaled_adversarial_loss: 0.0617 - val_loss: 0.1692 - val_sparse_categorical_crossentropy: 0.0999 - val_sparse_categorical_accuracy: 0.9621 - val_scaled_adversarial_loss: 0.0693\n",
      "Epoch 956/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.1184 - sparse_categorical_crossentropy: 0.0601 - sparse_categorical_accuracy: 0.9795 - scaled_adversarial_loss: 0.0583 - val_loss: 0.1931 - val_sparse_categorical_crossentropy: 0.1093 - val_sparse_categorical_accuracy: 0.9628 - val_scaled_adversarial_loss: 0.0837\n",
      "Epoch 957/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.1240 - sparse_categorical_crossentropy: 0.0616 - sparse_categorical_accuracy: 0.9790 - scaled_adversarial_loss: 0.0624 - val_loss: 0.1895 - val_sparse_categorical_crossentropy: 0.1094 - val_sparse_categorical_accuracy: 0.9599 - val_scaled_adversarial_loss: 0.0801\n",
      "Epoch 958/1000\n",
      "11/11 [==============================] - 4s 336ms/step - loss: 0.1194 - sparse_categorical_crossentropy: 0.0592 - sparse_categorical_accuracy: 0.9777 - scaled_adversarial_loss: 0.0602 - val_loss: 0.1823 - val_sparse_categorical_crossentropy: 0.1052 - val_sparse_categorical_accuracy: 0.9621 - val_scaled_adversarial_loss: 0.0772\n",
      "Epoch 959/1000\n",
      "11/11 [==============================] - 4s 331ms/step - loss: 0.1155 - sparse_categorical_crossentropy: 0.0557 - sparse_categorical_accuracy: 0.9803 - scaled_adversarial_loss: 0.0599 - val_loss: 0.1887 - val_sparse_categorical_crossentropy: 0.1119 - val_sparse_categorical_accuracy: 0.9576 - val_scaled_adversarial_loss: 0.0768\n",
      "Epoch 960/1000\n",
      "11/11 [==============================] - 4s 335ms/step - loss: 0.1199 - sparse_categorical_crossentropy: 0.0570 - sparse_categorical_accuracy: 0.9801 - scaled_adversarial_loss: 0.0629 - val_loss: 0.1900 - val_sparse_categorical_crossentropy: 0.1124 - val_sparse_categorical_accuracy: 0.9606 - val_scaled_adversarial_loss: 0.0776\n",
      "Epoch 961/1000\n",
      "11/11 [==============================] - 4s 335ms/step - loss: 0.1214 - sparse_categorical_crossentropy: 0.0628 - sparse_categorical_accuracy: 0.9769 - scaled_adversarial_loss: 0.0586 - val_loss: 0.1745 - val_sparse_categorical_crossentropy: 0.1012 - val_sparse_categorical_accuracy: 0.9599 - val_scaled_adversarial_loss: 0.0733\n",
      "Epoch 962/1000\n",
      "11/11 [==============================] - 4s 336ms/step - loss: 0.1211 - sparse_categorical_crossentropy: 0.0636 - sparse_categorical_accuracy: 0.9781 - scaled_adversarial_loss: 0.0574 - val_loss: 0.1886 - val_sparse_categorical_crossentropy: 0.1076 - val_sparse_categorical_accuracy: 0.9636 - val_scaled_adversarial_loss: 0.0810\n",
      "Epoch 963/1000\n",
      "11/11 [==============================] - 4s 336ms/step - loss: 0.1206 - sparse_categorical_crossentropy: 0.0619 - sparse_categorical_accuracy: 0.9790 - scaled_adversarial_loss: 0.0588 - val_loss: 0.1884 - val_sparse_categorical_crossentropy: 0.1120 - val_sparse_categorical_accuracy: 0.9584 - val_scaled_adversarial_loss: 0.0764\n",
      "Epoch 964/1000\n",
      "11/11 [==============================] - 4s 336ms/step - loss: 0.1200 - sparse_categorical_crossentropy: 0.0593 - sparse_categorical_accuracy: 0.9781 - scaled_adversarial_loss: 0.0607 - val_loss: 0.1816 - val_sparse_categorical_crossentropy: 0.1009 - val_sparse_categorical_accuracy: 0.9636 - val_scaled_adversarial_loss: 0.0807\n",
      "Epoch 965/1000\n",
      "11/11 [==============================] - 4s 336ms/step - loss: 0.1174 - sparse_categorical_crossentropy: 0.0548 - sparse_categorical_accuracy: 0.9808 - scaled_adversarial_loss: 0.0625 - val_loss: 0.1896 - val_sparse_categorical_crossentropy: 0.1080 - val_sparse_categorical_accuracy: 0.9569 - val_scaled_adversarial_loss: 0.0816\n",
      "Epoch 966/1000\n",
      "11/11 [==============================] - 4s 338ms/step - loss: 0.1253 - sparse_categorical_crossentropy: 0.0630 - sparse_categorical_accuracy: 0.9799 - scaled_adversarial_loss: 0.0623 - val_loss: 0.1823 - val_sparse_categorical_crossentropy: 0.1122 - val_sparse_categorical_accuracy: 0.9591 - val_scaled_adversarial_loss: 0.0701\n",
      "Epoch 967/1000\n",
      "11/11 [==============================] - 4s 335ms/step - loss: 0.1295 - sparse_categorical_crossentropy: 0.0686 - sparse_categorical_accuracy: 0.9777 - scaled_adversarial_loss: 0.0609 - val_loss: 0.1702 - val_sparse_categorical_crossentropy: 0.0966 - val_sparse_categorical_accuracy: 0.9613 - val_scaled_adversarial_loss: 0.0736\n",
      "Epoch 968/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.1170 - sparse_categorical_crossentropy: 0.0562 - sparse_categorical_accuracy: 0.9820 - scaled_adversarial_loss: 0.0608 - val_loss: 0.1737 - val_sparse_categorical_crossentropy: 0.1043 - val_sparse_categorical_accuracy: 0.9561 - val_scaled_adversarial_loss: 0.0694\n",
      "Epoch 969/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.1247 - sparse_categorical_crossentropy: 0.0631 - sparse_categorical_accuracy: 0.9781 - scaled_adversarial_loss: 0.0617 - val_loss: 0.1846 - val_sparse_categorical_crossentropy: 0.1073 - val_sparse_categorical_accuracy: 0.9591 - val_scaled_adversarial_loss: 0.0773\n",
      "Epoch 970/1000\n",
      "11/11 [==============================] - 4s 345ms/step - loss: 0.1282 - sparse_categorical_crossentropy: 0.0655 - sparse_categorical_accuracy: 0.9771 - scaled_adversarial_loss: 0.0627 - val_loss: 0.1750 - val_sparse_categorical_crossentropy: 0.1043 - val_sparse_categorical_accuracy: 0.9584 - val_scaled_adversarial_loss: 0.0708\n",
      "Epoch 971/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.1239 - sparse_categorical_crossentropy: 0.0632 - sparse_categorical_accuracy: 0.9781 - scaled_adversarial_loss: 0.0607 - val_loss: 0.1858 - val_sparse_categorical_crossentropy: 0.1098 - val_sparse_categorical_accuracy: 0.9576 - val_scaled_adversarial_loss: 0.0760\n",
      "Epoch 972/1000\n",
      "11/11 [==============================] - 4s 335ms/step - loss: 0.1235 - sparse_categorical_crossentropy: 0.0611 - sparse_categorical_accuracy: 0.9777 - scaled_adversarial_loss: 0.0624 - val_loss: 0.1614 - val_sparse_categorical_crossentropy: 0.0959 - val_sparse_categorical_accuracy: 0.9636 - val_scaled_adversarial_loss: 0.0655\n",
      "Epoch 973/1000\n",
      "11/11 [==============================] - 4s 341ms/step - loss: 0.1219 - sparse_categorical_crossentropy: 0.0594 - sparse_categorical_accuracy: 0.9807 - scaled_adversarial_loss: 0.0625 - val_loss: 0.1549 - val_sparse_categorical_crossentropy: 0.0936 - val_sparse_categorical_accuracy: 0.9591 - val_scaled_adversarial_loss: 0.0613\n",
      "Epoch 974/1000\n",
      "11/11 [==============================] - 4s 342ms/step - loss: 0.1196 - sparse_categorical_crossentropy: 0.0594 - sparse_categorical_accuracy: 0.9775 - scaled_adversarial_loss: 0.0602 - val_loss: 0.1698 - val_sparse_categorical_crossentropy: 0.1024 - val_sparse_categorical_accuracy: 0.9606 - val_scaled_adversarial_loss: 0.0673\n",
      "Epoch 975/1000\n",
      "11/11 [==============================] - 4s 336ms/step - loss: 0.1270 - sparse_categorical_crossentropy: 0.0644 - sparse_categorical_accuracy: 0.9788 - scaled_adversarial_loss: 0.0626 - val_loss: 0.1784 - val_sparse_categorical_crossentropy: 0.1063 - val_sparse_categorical_accuracy: 0.9628 - val_scaled_adversarial_loss: 0.0721\n",
      "Epoch 976/1000\n",
      "11/11 [==============================] - 4s 338ms/step - loss: 0.1243 - sparse_categorical_crossentropy: 0.0615 - sparse_categorical_accuracy: 0.9782 - scaled_adversarial_loss: 0.0628 - val_loss: 0.1769 - val_sparse_categorical_crossentropy: 0.1031 - val_sparse_categorical_accuracy: 0.9636 - val_scaled_adversarial_loss: 0.0738\n",
      "Epoch 977/1000\n",
      "11/11 [==============================] - 4s 336ms/step - loss: 0.1177 - sparse_categorical_crossentropy: 0.0584 - sparse_categorical_accuracy: 0.9807 - scaled_adversarial_loss: 0.0593 - val_loss: 0.2000 - val_sparse_categorical_crossentropy: 0.1150 - val_sparse_categorical_accuracy: 0.9599 - val_scaled_adversarial_loss: 0.0851\n",
      "Epoch 978/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.1167 - sparse_categorical_crossentropy: 0.0571 - sparse_categorical_accuracy: 0.9794 - scaled_adversarial_loss: 0.0596 - val_loss: 0.1764 - val_sparse_categorical_crossentropy: 0.1005 - val_sparse_categorical_accuracy: 0.9658 - val_scaled_adversarial_loss: 0.0759\n",
      "Epoch 979/1000\n",
      "11/11 [==============================] - 4s 338ms/step - loss: 0.1155 - sparse_categorical_crossentropy: 0.0548 - sparse_categorical_accuracy: 0.9801 - scaled_adversarial_loss: 0.0607 - val_loss: 0.1814 - val_sparse_categorical_crossentropy: 0.1060 - val_sparse_categorical_accuracy: 0.9599 - val_scaled_adversarial_loss: 0.0755\n",
      "Epoch 980/1000\n",
      "11/11 [==============================] - 4s 337ms/step - loss: 0.1125 - sparse_categorical_crossentropy: 0.0543 - sparse_categorical_accuracy: 0.9814 - scaled_adversarial_loss: 0.0583 - val_loss: 0.1814 - val_sparse_categorical_crossentropy: 0.1062 - val_sparse_categorical_accuracy: 0.9621 - val_scaled_adversarial_loss: 0.0751\n",
      "Epoch 981/1000\n",
      "11/11 [==============================] - 4s 335ms/step - loss: 0.1186 - sparse_categorical_crossentropy: 0.0577 - sparse_categorical_accuracy: 0.9805 - scaled_adversarial_loss: 0.0609 - val_loss: 0.1690 - val_sparse_categorical_crossentropy: 0.0996 - val_sparse_categorical_accuracy: 0.9621 - val_scaled_adversarial_loss: 0.0694\n",
      "Epoch 982/1000\n",
      "11/11 [==============================] - 4s 336ms/step - loss: 0.1165 - sparse_categorical_crossentropy: 0.0563 - sparse_categorical_accuracy: 0.9823 - scaled_adversarial_loss: 0.0602 - val_loss: 0.1640 - val_sparse_categorical_crossentropy: 0.0975 - val_sparse_categorical_accuracy: 0.9591 - val_scaled_adversarial_loss: 0.0666\n",
      "Epoch 983/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.1194 - sparse_categorical_crossentropy: 0.0573 - sparse_categorical_accuracy: 0.9794 - scaled_adversarial_loss: 0.0621 - val_loss: 0.1698 - val_sparse_categorical_crossentropy: 0.1016 - val_sparse_categorical_accuracy: 0.9599 - val_scaled_adversarial_loss: 0.0682\n",
      "Epoch 984/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.1182 - sparse_categorical_crossentropy: 0.0599 - sparse_categorical_accuracy: 0.9792 - scaled_adversarial_loss: 0.0584 - val_loss: 0.1841 - val_sparse_categorical_crossentropy: 0.1092 - val_sparse_categorical_accuracy: 0.9606 - val_scaled_adversarial_loss: 0.0749\n",
      "Epoch 985/1000\n",
      "11/11 [==============================] - 4s 335ms/step - loss: 0.1175 - sparse_categorical_crossentropy: 0.0582 - sparse_categorical_accuracy: 0.9792 - scaled_adversarial_loss: 0.0594 - val_loss: 0.1655 - val_sparse_categorical_crossentropy: 0.0983 - val_sparse_categorical_accuracy: 0.9606 - val_scaled_adversarial_loss: 0.0672\n",
      "Epoch 986/1000\n",
      "11/11 [==============================] - 4s 336ms/step - loss: 0.1128 - sparse_categorical_crossentropy: 0.0541 - sparse_categorical_accuracy: 0.9810 - scaled_adversarial_loss: 0.0587 - val_loss: 0.1793 - val_sparse_categorical_crossentropy: 0.1023 - val_sparse_categorical_accuracy: 0.9621 - val_scaled_adversarial_loss: 0.0771\n",
      "Epoch 987/1000\n",
      "11/11 [==============================] - 4s 339ms/step - loss: 0.1226 - sparse_categorical_crossentropy: 0.0627 - sparse_categorical_accuracy: 0.9782 - scaled_adversarial_loss: 0.0599 - val_loss: 0.1794 - val_sparse_categorical_crossentropy: 0.1073 - val_sparse_categorical_accuracy: 0.9591 - val_scaled_adversarial_loss: 0.0721\n",
      "Epoch 988/1000\n",
      "11/11 [==============================] - 4s 337ms/step - loss: 0.1132 - sparse_categorical_crossentropy: 0.0542 - sparse_categorical_accuracy: 0.9801 - scaled_adversarial_loss: 0.0590 - val_loss: 0.1830 - val_sparse_categorical_crossentropy: 0.1054 - val_sparse_categorical_accuracy: 0.9636 - val_scaled_adversarial_loss: 0.0776\n",
      "Epoch 989/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.1257 - sparse_categorical_crossentropy: 0.0659 - sparse_categorical_accuracy: 0.9795 - scaled_adversarial_loss: 0.0598 - val_loss: 0.1788 - val_sparse_categorical_crossentropy: 0.1114 - val_sparse_categorical_accuracy: 0.9599 - val_scaled_adversarial_loss: 0.0673\n",
      "Epoch 990/1000\n",
      "11/11 [==============================] - 4s 331ms/step - loss: 0.1223 - sparse_categorical_crossentropy: 0.0592 - sparse_categorical_accuracy: 0.9784 - scaled_adversarial_loss: 0.0630 - val_loss: 0.1854 - val_sparse_categorical_crossentropy: 0.1089 - val_sparse_categorical_accuracy: 0.9569 - val_scaled_adversarial_loss: 0.0764\n",
      "Epoch 991/1000\n",
      "11/11 [==============================] - 4s 331ms/step - loss: 0.1123 - sparse_categorical_crossentropy: 0.0516 - sparse_categorical_accuracy: 0.9825 - scaled_adversarial_loss: 0.0607 - val_loss: 0.1820 - val_sparse_categorical_crossentropy: 0.1083 - val_sparse_categorical_accuracy: 0.9628 - val_scaled_adversarial_loss: 0.0737\n",
      "Epoch 992/1000\n",
      "11/11 [==============================] - 4s 335ms/step - loss: 0.1210 - sparse_categorical_crossentropy: 0.0590 - sparse_categorical_accuracy: 0.9795 - scaled_adversarial_loss: 0.0620 - val_loss: 0.1726 - val_sparse_categorical_crossentropy: 0.1042 - val_sparse_categorical_accuracy: 0.9569 - val_scaled_adversarial_loss: 0.0684\n",
      "Epoch 993/1000\n",
      "11/11 [==============================] - 4s 337ms/step - loss: 0.1245 - sparse_categorical_crossentropy: 0.0634 - sparse_categorical_accuracy: 0.9790 - scaled_adversarial_loss: 0.0611 - val_loss: 0.1828 - val_sparse_categorical_crossentropy: 0.1062 - val_sparse_categorical_accuracy: 0.9621 - val_scaled_adversarial_loss: 0.0766\n",
      "Epoch 994/1000\n",
      "11/11 [==============================] - 4s 337ms/step - loss: 0.1171 - sparse_categorical_crossentropy: 0.0567 - sparse_categorical_accuracy: 0.9808 - scaled_adversarial_loss: 0.0605 - val_loss: 0.1877 - val_sparse_categorical_crossentropy: 0.1075 - val_sparse_categorical_accuracy: 0.9599 - val_scaled_adversarial_loss: 0.0802\n",
      "Epoch 995/1000\n",
      "11/11 [==============================] - 4s 333ms/step - loss: 0.1177 - sparse_categorical_crossentropy: 0.0561 - sparse_categorical_accuracy: 0.9801 - scaled_adversarial_loss: 0.0616 - val_loss: 0.1971 - val_sparse_categorical_crossentropy: 0.1184 - val_sparse_categorical_accuracy: 0.9576 - val_scaled_adversarial_loss: 0.0787\n",
      "Epoch 996/1000\n",
      "11/11 [==============================] - 4s 335ms/step - loss: 0.1211 - sparse_categorical_crossentropy: 0.0597 - sparse_categorical_accuracy: 0.9797 - scaled_adversarial_loss: 0.0613 - val_loss: 0.2058 - val_sparse_categorical_crossentropy: 0.1202 - val_sparse_categorical_accuracy: 0.9576 - val_scaled_adversarial_loss: 0.0856\n",
      "Epoch 997/1000\n",
      "11/11 [==============================] - 4s 335ms/step - loss: 0.1211 - sparse_categorical_crossentropy: 0.0560 - sparse_categorical_accuracy: 0.9814 - scaled_adversarial_loss: 0.0651 - val_loss: 0.1919 - val_sparse_categorical_crossentropy: 0.1122 - val_sparse_categorical_accuracy: 0.9636 - val_scaled_adversarial_loss: 0.0797\n",
      "Epoch 998/1000\n",
      "11/11 [==============================] - 4s 334ms/step - loss: 0.1191 - sparse_categorical_crossentropy: 0.0574 - sparse_categorical_accuracy: 0.9810 - scaled_adversarial_loss: 0.0616 - val_loss: 0.1871 - val_sparse_categorical_crossentropy: 0.1122 - val_sparse_categorical_accuracy: 0.9546 - val_scaled_adversarial_loss: 0.0749\n",
      "Epoch 999/1000\n",
      "11/11 [==============================] - 4s 336ms/step - loss: 0.1129 - sparse_categorical_crossentropy: 0.0511 - sparse_categorical_accuracy: 0.9827 - scaled_adversarial_loss: 0.0618 - val_loss: 0.1988 - val_sparse_categorical_crossentropy: 0.1188 - val_sparse_categorical_accuracy: 0.9599 - val_scaled_adversarial_loss: 0.0801\n",
      "Epoch 1000/1000\n",
      "11/11 [==============================] - 4s 336ms/step - loss: 0.1145 - sparse_categorical_crossentropy: 0.0523 - sparse_categorical_accuracy: 0.9842 - scaled_adversarial_loss: 0.0622 - val_loss: 0.2140 - val_sparse_categorical_crossentropy: 0.1224 - val_sparse_categorical_accuracy: 0.9613 - val_scaled_adversarial_loss: 0.0917\n"
     ]
    },
    {
     "data": {
      "text/plain": "<keras.callbacks.History at 0x1805bf93a00>"
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "adv_model.fit({'feature': X_train, 'label': y_train}, epochs=1000, batch_size=512, validation_data={'feature': X_test, 'label': y_test})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {
    "id": "Pmt7mlJoQ-Np",
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1345/1345 [==============================] - 9s 7ms/step - loss: 0.2178 - sparse_categorical_crossentropy: 0.1250 - sparse_categorical_accuracy: 0.9613 - scaled_adversarial_loss: 0.0929\n"
     ]
    },
    {
     "data": {
      "text/plain": "[0.21781371533870697,\n 0.12496182322502136,\n 0.9613382816314697,\n 0.0928516536951065]"
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "adv_model.evaluate({'feature': X_test, 'label': y_test}, batch_size=1)"
   ]
  }
 ],
 "metadata": {
  "colab": {
   "provenance": [],
   "mount_file_id": "1l_2YpamsRqa2kvQbF6VcRh1L-ZVNw2LN",
   "authorship_tag": "ABX9TyOZ6tqQxYPy3g7WnP4d6Wrs"
  },
  "kernelspec": {
   "display_name": "Python 3",
   "name": "python3"
  },
  "language_info": {
   "name": "python"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}